Based on the Grand Sum, the fear of public speaking was only ranked #45 (61.7%) out of 95 fears in the 2020/2021 Chapman Survey of American Fears

 

 

 

 

 

 

 

 

 

 

 

From 2014 to 2019 Chapman University produced an annual survey of American fears. They didn’t do one in 2020. In late September they produced results from a seventh survey with 95 questions, described as Wave 7 (2020/2021). It was done between January 5 and 15 of 2021 on a sample of 1035 U.S. adults, so it has a margin of error of plus or minus 3.0%. They asked how afraid people were, with four possible answers of Very Afraid, Afraid, Slightly Afraid, or Not Afraid. For some questions there were a few non-responses listed a Web Blank. As usual, they reported their results via a blog post listing the ranks based on the Sum of percentages for Very Afraid plus Afraid (which I discussed in my blog post on September 26, 2021).

 

Another way to report the results is with the percentages for Slightly Afraid also added, to produce a Grand Sum, as shown above. This produces larger, scarier numbers for marketing purposes (but is slightly silly for including that possibly insignificant fear level).    

 

Also, I calculated the Fear Score for each question (on a scale from 1 to 4, where 1= Not Afraid, 2=Slightly Afraid, 3=Afraid, and 4=Very Afraid), as I described in a blog post about the 2015 survey. The following list shows the ranking for the Grand Sum (T), the ranking for the Sum (S), the question, question number, percentage, and the Fear Score. In this case public speaking was ranked #45 at 61.7% (versus #54 and 29.0% for the Sum).

 

T01} S01] Corrupt government officials Q21b, 94.0% 3.175

T02} S05] Widespread civil unrest Q16n, 88.6% 2.717

T03} S04] People I love becoming seriously ill Q10b, 87.6% 2.732

T04} S07] Economic/financial collapse Q16l, 87.5% 2.681

T05} S02] People I love dying Q10d, 86.1% 2.744

T06} S21] Identity theft Q18o, 85.2% 2.476

T07} S03] A loved one contacting the coronavirus (COVID-19) Q28b, 85.1% 2.739

T08} S06] A pandemic or a major epidemic Q16m, 85.0% 2.681

T09} S08] Cyber-terrorism Q15c, 84.9% 2.565

T10} S12] A terrorist attack Q16s, 83.9% 2.546

T11} S09] Pollution of oceans, rivers and lakes Q13c, 82.2% 2.542

T12] S10] Biological warfare Q16r, 81.0% 2.547

T13} S15] The US becoming involved in another world war Q16o, 80.6% 2.523

T14} S32] Credit card fraud Q18p, 80.1% 2.331

T15} S28] Air pollution Q13a, 79.2% 2.354

T16} S37] Being hit by a drunk driver Q18e, 78.6% 2.313

T17} S25] Government use of drones within the US Q21a, 77.6% 2.355

T18} S14] Not having enough money for the future Q14a, 77.5% 2.539

T19} S16] Government tracking of personal data Q15e, 76.6% 2.441

T20} S17] Corporate tracking of personal data Q15d, 76.1% 2.397

T21} S22] Iran using nuclear weapons Q16u, 76.0% 2.400

T22} S18] Pollution of drinking water Q13b, 75.8% 2.375

T23} S20] Government interference with the coronavirus (COVID-19) vaccine approval Q21d, 75.7% 2.400

T24} S38] The collapse of the electrical grid Q16i, 75.4% 2.269

T25} S52] Theft of property Q18l, 75.2% 2.176

T26} S26] North Korea using nuclear weapons Q16t, 74.9% 2.388

T27} S33] Becoming seriously ill Q10a, 74.9% 2.286

T28} S34] Catching the coronavirus Q14g, 74.2% 2.305

T29} S27] A nuclear weapons attack Q16j, 73.9% 2.399

T30} S19] Extinction of plant and animal species Q13d, 73.5% 2.365

T31} S13] Global warming and climate change Q13f, 73.0% 2.452

T32} S31] Terrorism Q18r, 72.7% 2.331

T33} S47] Break-ins Q18k, 71.5% 2.163

T34} S11] Government restrictions on firearms and ammunition Q21c, 71.2% 2.443

T35} S36] Random/mass shooting Q18j, 70.9% 2.281

T36} S29] Contracting the coronavirus (COVID-19) Q28a, 70.8% 2.201

T37} S30] A nuclear accident/meltdown Q16k, 69.8% 2.271

T38} S24] High medical bills Q14e, 69.6% 2.340

T39} S46] Heights Q17m, 68.7% 2.139

T40} S41] Oil spills Q13e, 68.7% 2.122

T41} S40] A devastating drought Q16f, 66.9% 2.135

T42} S53] Dying Q10c, 65.0% 2.072

T43} S23] White supremacists Q19b, 64.0% 2.283

T44} S61] Mugging Q18a, 63.1% 2.028

T45} S54] Public speaking Q17n, 61.7% 2.023

T46} S39] A devastating wildfire Q16g, 61.6% 2.101

T47} S67] Reptiles (snakes, lizards, etc.) Q17d, 60.6% 1.980

T48} S62] Computers replacing people in the workforce Q15a, 60.3% 1.973

T49} S48] A devastating tornado Q16c, 59.7% 2.024

T50} S51] Sharks Q17f, 59.2% 2.010

T51} S43] A devastating earthquake Q16a, 58.8% 2.046

T52} S73] Walking alone at night Q17r, 58.8% 1.902

T53} S35] Right wing extremists Q19g, 58.1% 2.001

T54} S44] Racial/hate crime Q18i, 57.8% 2.064

T55} S75] Germs Q17h, 57.5% 1.864

T56} S70] Insects/arachnids (spiders, bees, etc.) Q17c, 57.1% 1.876

T57} S55] Murder by a stranger Q18c, 56.1% 2.009

T58} S45] A devastating hurricane Q16b, 55.6% 2.008

T59} S59] A devastating flood Q16d, 55.5% 1.964

T60} S63] Financial fraud Q18q, 55.5% 1.931

T61} S58] Gang violence Q18m, 55.3% 1.985

T62} S66] A devastating blizzard/winter storm Q16e, 52.6% 1.878

T63} S49] Not having enough money to pay my rent or mortgage Q14c, 50.5% 1.867

T64} S56] Left wing extremists Q19h, 50.2% 1.786

T65} S50] Police brutality Q18f, 49.1% 1.949

T66} S42] The Proud Boys Q19d, 48.6% 1.756

T67} S68] Deep lakes and oceans Q17i, 48.3% 1.848

T68} S77] Murder hornets Q17l, 48.2% 1.768

T69} S57] Being unemployed Q14d, 47.5% 1.654

T70} S86] Strangers Q17q, 47.1% 1.621

T71} S81] Small, enclosed spaces Q17o, 46.7% 1.698

T72} S82] Technology that I don’t understand Q15b, 46.2% 1.669

T73} S60] Sexual assault by a stranger Q18g, 45.6% 1.899

T74} S80] Catching influenza (the seasonal flu) Q14f, 44.7% 1.657

T75} S76] Illegal immigration Q16q, 42.9% 1.746

T76} S69] Stalking Q18b, 42.3% 1.772

T77} S65] Abduction/kidnapping Q18n, 42.0% 1.838

T78} S64] Losing your job due to the coronavirus (COVID-19) pandemic Q28c, 41.0% 1.807

T79} S72] Antifa Q19a, 39.8% 1.513

T80} S78] A large volcanic eruption Q16h, 37.7% 1.651

T81} S74] Murder by someone you know Q18d, 36.1% 1.709

T82} S85] Flying Q17j, 34.6% 1.515

T83} S71] Sexual assault by someone you know Q18h, 32.9% 1.696

T84} S83] Black Lives Matter (BLM) Q19c, 31.3% 1.529

T85} S84] Needles Q17b, 31.3% 1.474

T86} S95] Animals (dogs, rats, etc.) Q17e, 27.1% 1.332

T87} S79] Not being able to pay off the college debt of myself or a family member Q14b, 26.4% 1.010

T88} S87] Being caught in an embarrassing moment on Zoom or video conference Q14h, 25.6% 1.075

T89} S91] Blood Q17a, 24.9% 1.354

T90} S88] Ghosts Q17k, 24.4% 1.379

T91} S90] Whites no longer being the majority in the US Q16p, 21.7% 1.350

T92} S92] Muslims Q19f, 19.0% 1.269

T93} S89] Zombies Q17p, 17.6% 1.318

T94} S93] Immigrants Q19e, 15.9% 1.217

T95} S94] Clowns Q17g, 15.0% 1.220

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I was curious about whether the relative rankings shifted in going from the Sum to the Grand Sum. Only four fears had the exact same rank. A histogram for the differences is shown above. At a difference of 1 to 5 there are 26 changes versus – 1 to -5 where there are only 17 changes. Further negative, at larger differences, there is a fairly smooth curve.    

 

In the 2020/2021 Chapman Survey of American Fears, public speaking was only ranked #67 (11.5%) out of 95 fears at the Very Afraid level

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

From 2014 to 2019 Chapman University produced an annual survey of American fears. They didn’t do one in 2020. They just produced results from a seventh survey with 95 questions, described as Wave 7 (2020/2021). It was done between January 5 and 15 of 2021 on a sample of 1035 U.S. adults, so it has a margin of error of plus or minus 3.0%. They asked how afraid people were, with four possible answers of Very Afraid, Afraid, Slightly Afraid, or Not Afraid. For some questions there were a few non-responses listed a Web Blank. As usual, they reported their results via a blog post listing the ranks based on the sum of percentages for Very Afraid plus Afraid.

 

Another possible way to report the results is via the percentages for the Very Afraid level – those which scare the pants off people. I ranked the results for Very Afraid based on their detailed Methodology Report, and for comparison also listed those based on the sum for Very Afraid plus Afraid. For each question I calculated the Fear Score (on a scale from 1 to 4, where 1= Not Afraid, 2=Slightly Afraid, 3=Afraid, and 4=Very Afraid), as I described in a blog post about the 2015 survey. The following list shows the rank for Very Afraid (V), the rank for the sum of Very Afraid plus Afraid (S), the question and question number, the percentage for Very Afraid, and the Fear Score.

 

V01) S01] Corrupt government officials Q21b, 44.3% 3.175

V02) S03] A loved one contacting the coronavirus (COVID-19) Q28b, 31.2% 2.739

V03) S02] People I love dying Q10d, 29.9% 2.744

V04) S04] People I love becoming seriously ill Q10b, 28.4% 2.732

V05) S14] Not having enough money for the future Q14a, 27.9% 2.539

V06) S06] A pandemic or a major epidemic Q16m, 27.3% 2.681

V07) S05] Widespread civil unrest Q16n, 26.6% 2.717

V08) S07] Economic/financial collapse Q16l, 25.8% 2.681

V09) S11] Government restrictions on firearms and ammunition Q21c, 24.8% 2.443

V10) S23] White supremacists Q19b, 24.7% 2.283

V11) S10] Biological warfare Q16r, 24.5% 2.547

V12) S27] A nuclear weapons attack Q16j, 23.8% 2.399

V13) S13] Global warming and climate change Q13f, 23.7% 2.452

V14) S15] The US becoming involved in another world war Q16o, 23.5% 2.523

V15) S12] A terrorist attack Q16s, 22.0% 2.546

V16) S09] Pollution of oceans, rivers and lakes Q13c, 21.9% 2.542

V17) S31] Terrorism Q18r, 21.7% 2.331

V18) S24] High medical bills Q14e, 21.6% 2.340

V19) S16] Government tracking of personal data Q15e, 21.5% 2.441

V20) S26] North Korea using nuclear weapons Q16t, 21.4% 2.388

V21) S36] Random/mass shooting Q18j, 21.0% 2.281

V22) S08] Cyber-terrorism Q15c, 20.6% 2.565

V23) S22] Iran using nuclear weapons Q16u, 20.5% 2.400

V24) S20] Government interference with the coronavirus (COVID-19) vaccine approval Q21d, 20.5% 2.400

V25) S29] Contracting the coronavirus (COVID-19) Q28a, 19.4% 2.201

V26) S35] Right wing extremists Q19g, 19.1% 2.001

V27) S17] Corporate tracking of personal data Q15d, 18.8% 2.397

V28) S19] Extinction of plant and animal species Q13d, 18.7% 2.365

V29) S21] Identity theft Q18o, 18.6% 2.476

V30) S30] A nuclear accident/meltdown Q16k, 18.6% 2.271

V31) S49] Not having enough money to pay my rent or mortgage Q14c, 18.5% 1.867

V32) S34] Catching the coronavirus Q14g, % 18.3% 2.305

V33) S42] The Proud Boys Q19d, 17.7% 1.756

V34) S18] Pollution of drinking water Q13b, 17.6% 2.375

V35) S44] Racial/hate crime Q18i, 17.1% 2.064

V36) S60] Sexual assault by a stranger Q18g, 16.7% 1.899

V37) S65] Abduction/kidnapping Q18n, 16.4% 1.838

V38) S37] Being hit by a drunk driver Q18e, 16.2% 2.313

V39) S57] Being unemployed Q14d, 16.2% 1.654

V40) S33] Becoming seriously ill Q10a, 16.1% 2.286

V41) S55] Murder by a stranger Q18c, 15.9% 2.009

V42) S50] Police brutality Q18f, 15.8% 1.949

V43) S38] The collapse of the electrical grid Q16i, 15.7% 2.269

V44) S25] Government use of drones within the US Q21a, 15.3% 2.355

V45) S28] Air pollution Q13a, 14.9% 2.354

V46) S32] Credit card fraud Q18p, 14.8% 2.331

V47) S58] Gang violence Q18m, 14.7% 1.985

V48) S47] Break-ins Q18k, 14.6% 2.163

V49) S39] A devastating wildfire Q16g, 14.4% 2.101

V50) S71] Sexual assault by someone you know Q18h, 14.4% 1.696

V51) S46] Heights Q17m, 14.1% 2.139

V52) S45] A devastating hurricane Q16b, 14.0% 2.008

V53) S43] A devastating earthquake Q16a, 13.9% 2.046

V54) S56] Left wing extremists Q19h, 13.9% 1.786

V55) S40] A devastating drought Q16f, 13.7% 2.135

V56) S64] Losing your job due to the coronavirus (COVID-19) pandemic Q28c, 13.4% 1.807

V57) S74] Murder by someone you know Q18d, 13.4% 1.709

V58) S52] Theft of property Q18l, 13.0% 2.176

V59) S53] Dying Q10c, 12.8% 2.072

V60) S67] Reptiles (snakes, lizards, etc.) Q17d, 12.8% 1.980

V61) S59] A devastating flood Q16d, 12.6% 1.964

V62) S68] Deep lakes and oceans Q17i, 12.6% 1.848

V63) S61] Mugging Q18a, 12.3% 2.028

V64) S51] Sharks Q17f, 12.2% 2.010

V65) S48] A devastating tornado Q16c, 11.7% 2.024

V66) S69] Stalking Q18b, 11.6% 1.772

V67) S54] Public speaking Q17n, 11.5% 2.023

V68) S63] Financial fraud Q18q, 11.4% 1.931

V69) S72] Antifa Q19a, 11.1% 1.513

V70) S79] Not being able to pay off the college debt of myself or a family member Q14b, 11.0%  1.010

V71) S41] Oil spills Q13e, 10.8% 2.122

V72) S76] Illegal immigration Q16q, 10.4% 1.746

V73) S66] A devastating blizzard/winter storm Q16e, 10.2% 1.878

V74) S62] Computers replacing people in the workforce Q15a, 9.5% 1.973

V75) S73] Walking alone at night Q17r, 9.3% 1.902

V76) S78] A large volcanic eruption Q16h, 8.8% 1.651

V77) S83] Black Lives Matter (BLM) Q19c, 8.6% 1.529

V78) S77] Murder hornets Q17l, 8.6% 1.768

V79) S70] Insects/arachnids (spiders, bees, etc.) Q17c, 8.0% 1.876

V80) S75] Germs Q17h, 7.3% 1.864

V81) S81] Small, enclosed spaces Q17o, 7.2% 1.698

V82) S85] Flying Q17j, 5.7% 1.515

V83) S82] Technology that I don’t understand Q15b, 5.0% 1.669

V84) S89] Zombies Q17p, 4.9% 1.318

V85) S90] Whites no longer being the majority in the US Q16p, 4.7% 1.350

V86) S80] Catching influenza (the seasonal flu) Q14f, 4.4% 1.657

V87) S88] Ghosts Q17k, 4.2% 1.379

V88) S84] Needles Q17b, 4.2% 1.474

V89) S86] Strangers Q17q, 3.7% 1.621

V90) S87] Being caught in an embarrassing moment on Zoom or video conference Q14h, 3.5%  1.075

V91) S91] Blood Q17a, 2.7% 1.354

V92) S92] Muslims Q19f, 2.7% 1.269

V93) S94] Clowns Q17g, 2.3% 1.220

V94) S93] Immigrants Q19e, 2.2% 1.217

V95) S95] Animals (dogs, rats, etc.) Q17e, 1.6% 1.332

 

At 11.5% fear of public speaking ranks #67 - slightly below that for #66 stalking and slightly above #68 financial fraud. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I was curious about whether the relative rankings shifted in going from Very Afraid to the sum of Very Afraid plus Afraid. A histogram for the differences is shown above. At a difference of 1 to 5 there are 23 changes versus – 1 to -5 where there are only 15 changes. But at larger differences things are more symmetrical.    

 

The cartoon of a ‘pants down’ public speaker was modified from this one at Wikimedia Commons.

 

Fear of public speaking was only ranked #54 out of 95 fears in the 2020/2021 Chapman Survey of American Fears

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

From 2014 to 2019 Chapman University produced an annual survey of American fears. They didn’t do one in 2020. They just produced results from a seventh survey with 95 questions, described as Wave 7 (2020/2021). It was done between January 5 and 15 of 2021 on a sample of 1035 U.S. adults, so it has a margin of error of plus or minus 3.0%. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

They asked how afraid people were, with four possible answers of Very Afraid, Afraid, Slightly Afraid, or Not Afraid. For some questions there were a few non-responses listed a Web Blank. As usual, they reported their results via a blog post listing the ranks based on the sum of percentages for Very Afraid plus Afraid. I checked the results against those in their detailed Methodology Report. Also, I calculated the Fear Score for each question (on a scale from 1 to 4, where 1= Not Afraid, 2=Slightly Afraid, 3=Afraid, and 4=Very Afraid), as I described in a blog post about the 2015 survey. The following list shows the question, question number, their reported percentage, (the percentage sum from the Methodology Report), and the Fear Score.

 

1] Corrupt government officials Q21b, 79.6% (79.4%) 3.175

2] People I love dying Q10d, 58.5% (58.5%) 2.744

3] A loved one contacting the coronavirus (COVID-19) Q28b, 58.0% (57.8%) 2.739

4] People I love becoming seriously ill Q10b, 57.3% (57.3%) 2.732

5] Widespread civil unrest Q16n, 56.5% (56.5%) 2.717

6] A pandemic or a major epidemic Q16m, 55.8% (55.8%) 2.681

7] Economic/financial collapse Q16l, 54.8% (54.8%) 2.681

8] Cyber-terrorism Q15c, 51.0% (51.0%) 2.565

9] Pollution of oceans, rivers and lakes Q13c, 50.8% (50.2%) 2.542

10] Biological warfare Q16r, 49.3% (49.3%) 2.547

11] Government restrictions on firearms and ammunition Q21c, 48.9% (48.7%) 2.443

12] A terrorist attack Q16s, 48.8% (48.8%) 2.546

13] Global warming and climate change Q13f, 48.7% (48.6%) 2.452

14] Not having enough money for the future Q14a 48.6% (48.6%) 2.539

15] The US becoming involved in another world war Q16o, 48.3% (48.3%) 2.523

16] Government tracking of personal data Q15e, 45.6% (45.6%) 2.441

17] Corporate tracking of personal data Q15d, 44.9% (44.9%) 2.397

18] Pollution of drinking water Q13b, 44.6% (44.4%) 2.375

19] Extinction of plant and animal species Q13d, 44.4% (44.4%) 2.365

20] Government interference with the coronavirus (COVID-19) vaccine approval Q21d, 44.2% (44.0%) 2.400

21] Identity theft Q18o, 43.8% (43.8%) 2.476

22] Iran using nuclear weapons Q16u, 43.4% (43.4%) 2.400

23] White supremacists Q19b, 43.4% (43.2%) 2.283

24] High medical bills Q14e, 42.8% (42.8%) 2.340

25] Government use of drones within the US Q21a, 42.7% (42.7%) 2.355

26] North Korea using nuclear weapons Q16t, 42.5% (42.5%) 2.388

27] A nuclear weapons attack Q16j, 42.3% (42.2%) 2.399

28] Air pollution Q13a, 41.3% (41.3%) 2.354

29] Contacting the coronavirus (COVID-19) Q28a, 41.0% (37.8%) 2.201

30] A nuclear accident/meltdown Q16k, 38.7% (38.7%) 2.271

31] Terrorism Q18r, 38.7% (38.7%) 2.331

32] Credit card fraud Q18p, 38.5% (38.4%) 2.331

33] Becoming seriously ill Q10a, 38.3% (38.1%) 2.286

34] Catching the coronavirus Q14g, 38.0% (38.0%) 2.305

35] Right wing extremists Q19g, 37.2% (37.2%) 2.001

36] Random/mass shooting Q18j, 36.7% (36.5%) 2.281

37] Being hit by a drunk driver Q18e, 36.5% (36.5%) 2.313

38] The collapse of the electrical grid Q16i, 36.1% (36.0%) 2.269

39] A devastating wildfire Q16g, 34.1% (34.1%) 2.101

40] A devastating drought Q16f, 32.9% (32.9%) 2.135

41] Oil spills Q13e, 32.75 (32.7%) 2.122

42] The Proud Boys Q19d, 32.3% (32.3%) 1.756

43] A devastating earthquake Q16a, 32.0% (32.0%) 2.046

44] Racial/hate crime Q18i, 31.5% (31.5%) 2.064

45] A devastating hurricane Q16b, 31.4% (31.3%) 2.008

46] Heights Q17m, 31.2% (31.2%) 2.139

47] Break-ins Q18k, 31.0% (30.8%) 2.163

48] A devastating tornado Q16c, 31.0% (31.0%) 2.024

49] Not having enough money to pay my rent or mortgage Q14c, 30.7% (30.7%) 1.867

50] Police brutality Q18f, 30.1% (30.1%) 1.949

51] Sharks Q17f, 29.5% (29.5%) 2.010

52] Theft of property Q18l, 29.4% (29.4%) 2.176

53] Dying Q10c, 29.3% (29.3%) 2.072

54] Public speaking Q17n, 29.0% (29.0%) 2.023

55] Murder by a stranger Q18c, 28.9% (28.9%) 2.009

56] Left wing extremists Q19h, 28.9% (28.9%) 1.786

57] Being unemployed Q14d, 28.9% (28.9%) 1.654

58] Gang violence Q18m, 28.4% (28.4%) 1.985

59] A devastating flood Q16d, 28.3% (28.3%) 1.964

60] Sexual assault by a stranger Q18g, 27.6% (27.6%) 1.899

61] Mugging Q18a, 27.5% (27.4%) 2.028

62] Computers replacing people in the workforce Q15a, 27.5% (27.5%) 1.973

63] Financial fraud (such as a Ponzi SCheme, embezzlement, etc.) Q18q, 26.3% (26.3%) 1.931

64] Losing your job due to the coronavirus (COVID-19) pandemic Q28c, 26.3% (26.3%) 1.807

65] Abduction/kidnapping Q18n, 25.6% (25.5%) 1.838

66] A devastating blizzard/winter storm Q16e, 25.3% (25.2%) 1.878

67] Reptiles (snakes, lizards, etc.) Q17d, 24.7% (24.7%) 1.980

68] Deep lakes and oceans Q17i, 24.7% (24.5%) 1.848

69] Stalking Q18b, 23.3% (23.3%) 1.772

70] Insects/arachnids (spiders, bees, etc.) Q17c, 22.8% (22.7%) 1.876

71] Sexual assault by someone you know Q18h, 22.4% (22.4%) 1.696

72] Antifa Q19a, 22.1% (22.1%) 1.513

73] Walking alone at night Q17r, 22.1% (22.1%) 1.902

74] Murder by someone you know Q18d, 21.8% (21.6%) 1.709

75] Germs Q17h, 21.7% (21.7%) 1.864

76] Illegal immigration Q16q, 21.5% (21.4%) 1.746

77] Murder hornets Q17l, 20.1% (20.1%) 1.768

78] A large volcanic eruption Q16h, 18.9% (18.9%) 1.651

79] Not being able to pay off the college debt of myself or a family member Q14b, 18.3% (18.3%) 1.010

80] Catching influenza (the seasonal flu) Q14f, 16.7% (16.7%) 1.657

81] Small, enclosed spaces Q17o, 16.2% (16.2%) 1.698

82] Technology that I don’t understand Q15b, 15.9% (15.9%) 1.669

83] Black Lives Matter (BLM) Q19c, 14.7% (14.7%) 1.529

84] Needles Q17b, 11.9% (11.9%) 1.474

85] Flying Q17j, 11.5% (11.5%) 1.515

86] Strangers Q17q, 11.4% (11.4%) 1.621

87] Being caught in an embarrassing moment on Zoom or video conference Q14h, 9.8% (9.8%) 1.075

88] Ghosts Q17k, 9.3% (9.3%) 1.379

89] Zombies Q17p, 9.3% (9.3%) 1.318

90] Whites no longer being the majority in the US Q16p, 8.7% (8.7%) 1.350

91] Blood Q17a, 8.7% (8.1%) 1.354

92] Muslims Q19f, 6.8% (6.8%) 1.269

93] Immigrants Q19e, 5.8% (5.8%) 1.217

94] Clowns Q17g, 5.6% (5.6%) 1.220

95] Animals (dogs, rats, etc.) Q17e, 4.6% (4.6%) 1.332

 

Most of the percentages agree with the Methodology Report, but others are slightly higher and include the Web Blank. #29 Contacting the coronavirus (COVID-19) Q28a, 41.0% and #34 Catching the coronavirus Q14g, 38.0% really asked the same thing.

 

At 29.0% fear of public speaking ranks #54 - slightly below that for #51 sharks and #52 theft of property (both 29.5%), and #53 dying (29.3%).

 

There is some curious data for Q14, Q19, and Q28a. For Q28a the Methodology Report shows Missing System of 82 (7.9%) instead of a Web Blank, and has the Valid Percent column rescaled based on a total of 953 rather than 1035. 

 

 

 

 

 

 

 

 

 

 

 

 

As shown above in a table, for Q14b, Q14c, Q14d, and Q14h there are significant percentages shown for Doesn’t apply to me, but no rescaling to produce Valid Percent. 

 

 

 

 

 

 

 

 

 

 

 

 

As shown above in another table, for Q19 there also are significant percentages shown for I don’t know who/what this is, but again no rescaling to produce Valid Percent.

 

In most cases the Fear Scores rank similarly to the sum for Very Afraid plus Afraid, except for the results shown above in those two tables.

 

The cartoon of a public speaker was modified from this one at Wikimedia Commons.

 

What shape should your next year be? Modeling dough as a metaphorical prop.

 

 

 

 

 

 

 

 

 

 

 

 

I recently saw a six-minute YouTube video by Brooke Samples from January 29, 2017 titled Props for speeches. After 3 -1/2 minutes she says:    

 

“And last week, at the Palm Beach Advanced Toastmasters, we had the Play-Doh metaphor, as far as what do you want your year to look like? You have the opportunity to shape it whatever way you want to. You can make it a cookie man or something. This kind of prop makes your point more memorable. 

 

Cathy Frasier could have spoken all night long about the opportunities 2017 allows us. But this one visual of Play-Doh and how you make it this way, you don’t like it, you wad it up and start over.

 

I like that so much that when I was in Houston last week speaking to sixty service managers, parts managers, general managers, and controllers, I got every one of them their own Play-Doh, And I put a reminder on there that your future is flexible, and if it doesn’t work out, start over again, and it’s fun.”      

 At a local Dollar Tree store I found ten-ounce bags of generic modeling dough like the yellow shown above. If you wanted to hand out cans to your audience, then at Amazon there is a pack of ten 2-ounce cans for $7.99.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Another way to begin using this as a prop would be to shape the dough into a question mark, as is shown above.  

 

Scaring people using ‘big’ numbers from the Vaccine Adverse Event Reporting System (VAERS)

 

After is not the same as because of

 

At Natural News on September 15, 2021 there is an article by Lance D. Johnson titled Approximately 70 people die from COVID vaccines every day in America – VAERS data. Is that claim true? No! Natural News is an unreliable source of anti-vaccine information, as was discussed by Melissa Goldin, John Gregory, and Kendrick McDonald at Newsweek on May 25, 2021 in an article titled How a well-meaning U.S. government database fuels dangerous vaccine misinformation. The VAERS web page titled Guide to Interpreting VAERS Data explains that:

 

“A report to VAERS generally does not prove that the identified vaccine(s) caused the adverse event described. It only confirms that the reported event occurred sometime after vaccine was given. No proof that the event was caused by the vaccine is required in order for VAERS to accept the report. VAERS accepts all reports without judging whether the event was caused by the vaccine.”

 

And another article by David L. Katz at LinkedIn Pulse on July 13, 2021 titled COVID and Vaccine Adverse Event Reporting: How VAERS veers off course adds:

 

“Even if a vaccine actually caused not a single death, VAERS would be loaded up with reports of death that occurred following vaccination, from a variety of causes. VAERS is designed to be inclusive, not exclusive; to be sensitive, not specific. VAERS is designed to welcome false positives, to avoid the dangers of false negatives. VAERS is highly prone to mix together actual ‘cause and effect’ with ‘true, true, and entirely unrelated.’ These are, simply, facts of the system, there by design.”

 

How many people die every day? A fact check article by Bill McCarthy at Politifact on May 6, 2021 titled Tucker Carlson’s misleading claim about deaths after COVID-19 vaccine says 8,000 people die from all causes.

 

Questionable reports in VAERS

 

The least credible report in VAERS was discussed by James R. Laidler in an archived article from his neurodiversity weblog back on July 27, 2006 titled Chelation & Autism which stated:

 

“The chief problem with VAERS data is that reports can be entered by anyone and are not routinely verified. To demonstrate this a few years ago I entered a report that an influenza vaccine had turned me into The Hulk. The report was accepted and entered into the database. Because the reported adverse event was so … unusual, a representative of VAERS contacted me. After a discussion of the VAERS database and its limitations, they asked my permission to delete the record, which I granted. If I had not agreed, the record would still be there still, showing that any claim can become part of the database, no matter how outrageous or improbable.”

 

An article by Jonathan Jarry at the McGill Office for Science and Society on June 18, 2021 titled Don’t Fall for the ‘VAERS Scare’ Tactic mentions other questionable reports: 

 

“To show that VAERS listings should not be taken at face value to mean that the vaccine caused the reported event, I trawled through the database’s reports on the COVID-19 vaccines. There were many, many reports of fever and injection site reactions (to be expected), but there were also, shall we say, head-scratching reports. A woman reported a large bald spot on top of her head following vaccination. Someone simply wrote in, ‘Nosebleed.’ I saw a report of ‘anal leakage.’ More than one person complained of suddenly becoming impotent. Meanwhile, at the other end of the spectrum, the funniest report I saw stated, ‘My penis swelled to ten times its size.’ ”

 

How do the numbers of adverse events compare with the number of people vaccinated?

 

Some people proclaim that thousands or hundreds of thousands of adverse events have occurred. But those apparently large numbers need to be considered as a ratio (or percent) by dividing by the number of people which were vaccinated – hundreds of millions. We can look at an example from Idaho. An article by Bob “Nugie” Neugebauer at the Gem State Patriot News on July 17, 2021 titled Vaccination or termination reported that there were 438,441 total adverse events with 41,015 serious injuries and 9048 deaths. At that time there had been 156,982,549 people fully vaccinated.

 

 

 

 

 

 

 

 

 

 

The table shown above gives the fraction of events compared with the number vaccinated, and multiplies by 100 to give the percentage. It also shows the reciprocal of the fraction, the odds of each event. The usual yardstick for a rare event is being struck by lightning. According to the National Weather Service the lifetime fraction is 0.00006356, which is bigger than the 0.0000576 for death after a COVID vaccination. The 41,015 serious injuries is a fraction of only 0.000261, or odds of 1 in 3,827. Yet Neubauer’s second paragraph instead had claimed:

   

“This is going to become a huge problem for employers who force their employees to take the shot as they may wind up assuming some if not all of the liability for any injuries that occur to their employees who required to take the shot. IACI’s president Alex LeBeau says that any incidents occurring from the vaccine should be covered by workmen’s compensation. You can bet that the courts are going to be full of cases where employers are going to be sued by employees for injuries caused by this covid medical device.”

 

Are there other databases better than VAERS?

 

Yes, of course there are. An article by Jonathan Howard at Science-Based Medicine on September 16, 2021 titled More thoughts on the VAERS pre-print mentions the Vaccine Safety Datalink (VSD):

 

“The VSD is an active monitoring system that is directly linked to patients’ medical records.  As such, it is not subject to the same limitations as VAERS, a passive monitoring system that contains unverified and possibly duplicate cases.”

 

The cartoon of a scared man was modified from this one at Wikimedia Commons.

 

Another fairy tale about election fraud from Donald Trump

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

On September 13, 2021 Donald J. Trump whined:

 

“Does anybody really believe the California Recall Election isn’t rigged? Millions and millions of Mail-In Ballots will make this just another giant Election Scam, no different, but less blatant, than the 2020 Presidential Election Scam!”

 

That same day at Politifact Amy Sherman had an article that discussed how Trump and his allies lack evidence for claim about ‘rigged’ California recall.

 

The next day Trump got more specific and said it was totally rigged:

 

“….In any event, it all doesn’t matter because the California Election is totally Rigged. Many people are already complaining that when they go to vote they are told, ‘I’m sorry, you already voted’ (Just like 2020, among many other things). They then leave angry, but fortunately, even the Fake News Media has been reporting it.” 

 

But that day at Politifact another article by Tom Kertscher discussed how in Woodland Hills a Snafu at voting site did not target GOP voters in Calif. recall election. Those voters got to submit provisional ballots anyhow. On September 15, 2021 there was an AP article by Adam Beam titled Few voting issues reported with California recall election. And at Newsweek there was an article by Anders Anglesey titled Larry Elder concedes California recall election as vote fraud plan goes up in smoke.

 

At FiveThirtyEight on September 14, 2021 an article titled Latest polls of the California recall election had reported 57.3% wanted to keep the governor, versus 41.5% who wanted to remove him (a 15.8% lead, versus the situation in early August with a tie at ~47%).

 

What was the result of this recall election? 63.7% voted to keep the governor, versus 36.3% who voted to remove him. Does that look rigged? No, it agrees well with the voter registration results from the end of August. There were 46.5% registered Democrats, 24.0% registered Republicans, 23.2% with no party preference, and 6.3% other. If we simply split the 23.2% and 6.3% and add them to the partisan totals, then we get 61.3% for keeping the governor and 38.7% for removing him – within 3% of the actual voting.  

 

An image of a wolf and Red Riding Hood came from Wikimedia Commons.

 

Are you stuck in a rut?

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The September/October 2021 issue of Speaker magazine has a useful article by April Callis Birchmeier on pages 30 to 35 titled Feeling Stuck? It’s Time to Bust a Rut. On page 34 she discusses these 7 strategies and tactics to get unstuck:

1] Move.

2] The tin man – WD-40.

3] Get to the root.

4] Phone a friend.

5] Create accountability.

6] Location. Location. Location.

7] Take 10.

 

On April 15, 2021 at Psychology Today there is second article by Nick Morgan titled Three tricks from psychology that could improve your life (Research shows how to get out of mental ruts and improve your mood).

 

Toastmasters club meetings also can get stuck in a rut. The September 2019 issue of Toastmaster magazine has a third article by Craig Harrison on pages 16 to 19 titled Infuse Your Club with Vitamin C: Creativity. (A very similar article with that title also had appeared on pages 16 to 18 of the January 2009 issue).

 

You also can get stuck when writing a speech. On February 23, 2020 I blogged about Finding speech topics and doing research. The October 2015 issue of Toastmaster magazine has a fourth brief article by Kathleen Fordyce on page 27 titled 3 Ways to Shake Off Writer’s Block.

 

The image of a thinking man was adapted from this cartoon at Wikimedia Commons.

 

What goes wrong during video or audio calls, and the consequences – Zoom, gloom, and doom

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I saw an article by Rachel Layne at CBS News on September 2021 titled Afraid a Zoom blunder will get you fired? 1 in 4 bosses have justified that fear, survey finds. It discussed an online survey done by Wakefield Research for Vyopta between July 30, 2021 and August 10, 2021. Detailed results are reported here. They conducted a survey with 15 questions on 200 U.S. executives (ranked VP or above) at companies with 500+ employees. That’s a relatively small sample, so the margin of error is about 6.9%. More commonly a sample size of 1000 would be used for a margin of error of 3.1%.

 

 

 

 

 

 

 

 

 

 

 

The fifth question was about which of the following had ever happened at your company due to technology or connection issues. As shown above in a bar chart, 75% had to reschedule a meeting, 41% had missed a project deadline, 32% had lost a client or business opportunity, and just 15% had none of the above (while 86% had any of the first three).   

 

 

 

 

 

 

 

 

 

 

 

The ninth question was about which of seven issues had ever happened due to problems with virtual connection technology. As shown above in a second bar chart, 50% had difficulty hearing or understanding a speaker, and 28% had been unable to record a call.

 

 

 

 

 

 

 

 

 

 

 

The seventh question was about which of the following had ever happened at your company as a result from staff member’s error during an audio or video call. Five answers, shown above in a third bar chart, were as follows: 53% moved responsibility for setting up calls to another staff member, 40% were given an informal reprimand, 38% were given a formal reprimand, 38% had removed a staff member from a project, and 24% had fired a staff member. The fired category also has been termed “zoom and doom.”

 

The image was adapted from this cartoon at Wikimedia Commons.

 

What you think is cool may be way more than what your audience needs to know

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

On September 6, 2021 I received an email from editor Ella Miller in New Hampshire regarding my blog post from way back on February 10, 2009 titled Christmas camouflage graphics: how to lose ~5% of your audience with just 2 mouse clicks. In that post I had linked to the Wikipedia article on Color blindness. She pointed out a new article from August 9, 2021 at MYeyebb titled Everything you need to know about color blindness and suggested I might instead link to it. (An article at The PowerPoint Blog on August 16, 2021 titled Color Blindness in Depth already had linked to that new article).

 

But my February 10, 2009 post was the very first in a series of a half-dozen about avoiding color choices in PowerPoint slides that would confuse a minority of people (mostly men) who had red-green color blindness. It was followed by a second on March 13, 2009 titled An example of “Christmas Camouflage” graphics, a third on April 24, 2009 titled Watch haw u kuler ur slidez: a “Christmas Camouflage” Trifecta, a fourth on November 3, 2009 titled Another example of Christmas camouflage graphics, a fifth on December 8, 2011 titled ‘Tis the season for Christmas Camouflage in graphics, and a sixth on December 20, 2014 titled Christmas Camouflage and why you shouldn’t copy anyone’s slides without thinking first.

 

Readers of my blog didn’t need to know everything about color blindness. They only needed to know how to avoid confusing audiences for their PowerPoint presentations. Since my last post on December 20, 2014 there has been an excellent article by Dave Paradi at Think Outside the Slide on February 3, 2015 titled Testing how a slide looks to someone with a color deficiency; Issue #330. Dave describes using the Coblis Color Blindness Simulator rather than the Vischeck online tool which I had discussed.

 

It is easy to put more information into a presentation than the audience needs to know. On July 12, 2019 I blogged about Chekhov’s Gun – speechwriting advice from a cartoon. That famous Russian playwright once had proclaimed that:

“One must not put a loaded rifle on the stage if no one is thinking of firing it.”

 

Bogus claims in a press release about a ‘new’ public speaking book

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

On September 8, 2021 my Google Alert on the phrase “public speaking” included a press release at PR. com (and AP News) titled The Plague of Public Speaking Anxiety Has Met Its Match. It discusses a ‘new’ book by Sean Tyler Foley titled The Power to Speak Naked. That same release also appeared at PRweb with a provocative different title, Controversial book banned by Amazon now available in bookstores. But Foley’s book was NOT banned by Amazon – it appears right here, as does the previous version from 2019 (noted as a #1 bestseller).

 

The second paragraph in the press release says:  

 

“The statistics say it all. Fear of public speaking has 10% impairment on one’s wages and 15% on promotions and 90% of public speaking anxiety comes from lack of preparation. With ‘The Power to Speak Naked,’ anyone can learn to unleash the power to speak confidently and step apart from the 255 million Americans who have public speaking anxiety.”

 

Claims that public speaking fear has a 10% impairment on wages and 15% on promotions are bogus – those statistics really are for social anxiety disorder. I blogged about them in a post on December 15, 2016 titled Believable and unbelievable statistics about fears and phobias of public speaking.

 

Do 255 million Americans have public speaking anxiety? No! That number is what you get when you take 77% of the 2020 census number for the U.S. population (331,449,281 million). On October 12, 2020 I posted with the title Do 77% of Americans fear public speaking? No! That percentage described stage fright in Swedes who also had social anxiety disorder.

 

The second sentence of the press release has a typo. It says that:

 

“This was a common tip for people with stage freight(sic) to try and calm their nerves.”

 

Way back on November 12, 2009 I blogged about Stage freight and other true typos or yakwirms. Yakwirm is an acronym for You All Know What I Really Meant.

 

Don’t AWE your audience by using Acronyms Without Explanations

 

 

 

 

 

 

 

 

 

 

 

 

At her Maniactive blog on August 9, 2021 there is an excellent brief post by Laura Bergells titled AWE: Acronyms Without Explanation!. Using an acronym without defining it first is an awful use of jargon. It indicates you think that is NMJ (Not My Job) but it is. On July 5, 2019 I blogged about how The first time you use an acronym you need to define it.

 

Acronyms sometimes have multiple meanings. Recently many people would say that BLM obviously means Black Lives Matter. But in states like Nevada, Utah, and Idaho the older meaning is the federal Bureau of Land Management. In Nevada 81.1% of land is federally owned. Of that 83.9% is by that BLM and 10.1% % is U.S. Forest Service. In Utah 66.5% of land is federally owned. Of that 65.2% is BLM and 23.4% % is U.S. Forest Service. Here in Idaho 61.7% of land is federally owned. Of that 62.7% is U.S. Forest Service, and 35.6% is BLM. 

 

The image was adapted from a cartoon of a woman presenting a sales flow chart at Wikimedia Commons.

 

Eight idioms in a comic strip

 

 

 

 

 

 

 

The September 1, 2021 Sheldon comic by Dave Kellet opened with Arthur, the talking duck, spouting the dialogue shown above. (I added the arrows). Then he added six more idioms: what’s shakin’, what’s bakin’, what’s movin’, what’s groovin’, how’s it goin’, and how’s it hangin’.