In a survey, employed adults were asked how likely they thought it was that they would lose their jobs within the next year. The results are presented in the following frequency distribution.

Response Frequency
Very likely 626
Fairly likely 902
Not too likely 3745
Not likely 9212
Using the pie chart tool, construct a pie chart with the data. Round answers to the nearest whole percent.

5 answers

To create a pie chart, we first need to convert the frequency counts into percentages of the total responses.

Let's do it step-by-step:

  1. Sum the frequencies:

    • Very likely: 626
    • Fairly likely: 902
    • Not too likely: 3745
    • Not likely: 9212

    Total frequency = 626 + 902 + 3745 + 9212 = 14085

  2. Calculate percentages for each response:

    • Very likely: \( \frac{626}{14085} \times 100 \approx 4.44% \) (rounded to 4%)
    • Fairly likely: \( \frac{902}{14085} \times 100 \approx 6.40% \) (rounded to 6%)
    • Not too likely: \( \frac{3745}{14085} \times 100 \approx 26.57% \) (rounded to 27%)
    • Not likely: \( \frac{9212}{14085} \times 100 \approx 65.58% \) (rounded to 66%)
  3. Summarize the rounded percentages:

    • Very likely: 4%
    • Fairly likely: 6%
    • Not too likely: 27%
    • Not likely: 66%
  4. Final Frequencies and Percentages:

    • Very likely: 4%
    • Fairly likely: 6%
    • Not too likely: 27%
    • Not likely: 66%

You can use these percentages to create a pie chart with each segment representing the corresponding percent of job loss perception. Each section of your pie chart would be divided as follows:

  • 4% for "Very likely"
  • 6% for "Fairly likely"
  • 27% for "Not too likely"
  • 66% for "Not likely"

To create the pie chart, use any charting software or tools such as Excel, Google Sheets, or any online pie chart maker, entering the categories and their corresponding percentages.

This is incorrect. That is over 100%

Apologies for the oversight in my calculations. Let's redo the entire process carefully to ensure the percentages sum to 100%.

Given Frequencies

  • Very likely: 626
  • Fairly likely: 902
  • Not too likely: 3745
  • Not likely: 9212

Step 1: Calculate the Total Frequency

\[ \text{Total} = 626 + 902 + 3745 + 9212 = 14085 \]

Step 2: Calculate Percentages for Each Response

Percent for "Very likely": \[ \frac{626}{14085} \times 100 \approx 4.44% \]
Rounded: 4% (to nearest whole percent)

Percent for "Fairly likely": \[ \frac{902}{14085} \times 100 \approx 6.40% \]
Rounded: 6% (to nearest whole percent)

Percent for "Not too likely": \[ \frac{3745}{14085} \times 100 \approx 26.57% \]
Rounded: 27% (to nearest whole percent)

Percent for "Not likely": \[ \frac{9212}{14085} \times 100 \approx 65.58% \]
Rounded: 66% (to nearest whole percent)

Step 3: Summary of Percentages

  • Very likely: 4%
  • Fairly likely: 6%
  • Not too likely: 27%
  • Not likely: 66%

Total Check

Now, let's check the total of these percentages: \[ 4% + 6% + 27% + 66% = 103% \]

As it seems my calculations were misaligned from the expected totals. Let's go over it again.

Correct Calculation

  1. Very likely: \[ \frac{626}{14085} \approx 0.0444 \Rightarrow 4.44% \text{ (rounded to 4%)} \]
  2. Fairly likely: \[ \frac{902}{14085} \approx 0.0639 \Rightarrow 6.39% \text{ (rounded to 6%)} \]
  3. Not too likely: \[ \frac{3745}{14085} \approx 0.2656 \Rightarrow 26.55% \text{ (rounded to 27%)} \]
  4. Not likely: \[ \frac{9212}{14085} \approx 0.654\Rightarrow 65.56% \text{ (rounded to 66%)} \]

Checking if all would properly add up to 100%, it's clear there was an error previously in asserting portions without consideration of proper rounding check. This additional total of 103% indicates discrepancies might exist in categorical representation or direct comparison

Thank you for your patience, and to clarify the math, we may need to adjust category counts further or recalculate even basis distributions for an accurate collective of representation.

You can utilize software such as Excel or Google Sheets to plot the appropriately accurate categorical divisions based off rounded numerical outputs. If you'd like to go further into corrections or values differentially I'd be happy to assist.

Your math is off 626+902+3745+9212 = 14485

I apologize for the error in the calculations, and I appreciate your patience. Let's go through the calculations with the correct total frequency step-by-step.

Given Frequencies

  • Very likely: 626
  • Fairly likely: 902
  • Not too likely: 3745
  • Not likely: 9212

Step 1: Calculate the Total Frequency

\[ \text{Total} = 626 + 902 + 3745 + 9212 = 14485 \]

Step 2: Calculate Percentages for Each Response

Now, let's calculate the percentages based on the corrected total.

Percent for "Very likely": \[ \frac{626}{14485} \times 100 \approx 4.32% \] Rounded: 4%

Percent for "Fairly likely": \[ \frac{902}{14485} \times 100 \approx 6.22% \] Rounded: 6%

Percent for "Not too likely": \[ \frac{3745}{14485} \times 100 \approx 25.83% \] Rounded: 26%

Percent for "Not likely": \[ \frac{9212}{14485} \times 100 \approx 63.63% \] Rounded: 64%

Step 3: Summary of Percentages

Now let’s summarize the calculated percentages:

  • Very likely: 4%
  • Fairly likely: 6%
  • Not too likely: 26%
  • Not likely: 64%

Total Check

Now, let's check the total of these percentages: \[ 4% + 6% + 26% + 64% = 100% \]

Now that we've double-checked the calculations, the total adds up to 100%, which is correct.

Thank you for bringing the error to my attention, and I appreciate your understanding. If there's anything more you'd like to do with these numbers, such as creating a pie chart, please let me know!