<p> NAME______ID:</p><p>Homework 3c: Computational Review – Key , Test #1 (open book)</p><p>1. A researcher records the following scores in a pilot 2. Assume SS = 2468 and n equals 20. Calculate standard study: 10, 12, 14, 10, 12, 16. Calculate variance. deviation.</p><p> x2 742  x 2  940  sˆ  n  6 SS 2468 x n 1 6 1 sˆ   x n 1 20 1</p><p>Always report correct symbol. 2 ŝx = 5. 4 6 6 7 ŝx = 1 1. 3 9 7 1</p><p>3. A traffic safety engineer measured the number of times 4. Calculate σ if σ2 = 16 and n=35. motorists ran a read light at various 20 minute intervals throughout the day. Calculate standard deviation for these numbers: 2, 0, 4, 1, 0, 5, 9 2 2 2 16 4  x 21  x      x 2  127  sˆ  n  7 x n 1 7 1</p><p> sˆx  3.2650</p><p>5. Open the website dataset Test 1 Review. Using SPSS, 6. Using SPSS, create a graph showing the frequency for construct an appropriate graph to show the average hours hours of exercise. Do NOT produce a bar chart. Label of work plus/minus one standard deviation. Roughly appropriately. sketch the graph below and label the axes appropriately.</p><p>60 6 s r y k</p><p> u 5 c e o e n 4 H</p><p>50 e</p><p> w</p><p> u</p><p> r 3 D q e S</p><p> e 2 p</p><p> r 1</p><p>40 d - F 1 e +</p><p> k 0 r n o a 30 0 2.5 5 7.5 10 … Mean e w =6.9 M hrsexer Std. … Hours worked per week</p><p>Go to Error bar, select separate variables, select Standard Deviation and set multiplier to Go to Graph, histogram, move hrsexer into 1. “variable” box. 7. Using SPSS, create a graph comparing the average 8. Using SPSS, create a graph comparing the hours hours of work and exercise. exercised by single and married persons.</p><p>50</p><p>40 8 r e n</p><p> x 6 30 e a s e r</p><p> h 4</p><p>M 20 n a</p><p> e 2</p><p>10 M 0 0 single married Hours worked hrsexer per week Marital status</p><p>Go to graph, bar, separate variables, select Go to graph, bar, groups of cases, select hours of work and hours of exercise, marriage for category axis, select “other summary function” for upper box and move in hours of exercise,</p><p>9. Produce a table comparing the Hours Exercised by 10. Report the median Hours Worked and Hours single and married persons. Exercised.</p><p>Avg. Hours Single= 6.00 Hours Worked Md = 40.00 Avg. Hours Married= 7.80 Hours Exercised Md = 8.00</p><p>Use Analyze, compare means, means Go to descriptives, frequencies, select statistics, select median</p><p>11. Report the largest standard deviation among the four 12. Report the Pearson Correlation Coefficient of the quantitative variables in the dataset. variable that best predicts Hours Exercised. </p><p>ŝx = 1 4. 2 4 4 r = -.7 7 4</p><p>Use Analyze, descriptives, descriptives. Correlations</p><p>Social Hours worked Support anxiety per week quality hrsexer anxiety Pearson Correlation 1 .194 .530* -.774** Sig. (2-tailed) .413 .016 .000 N 20 20 20 20 Hours worked per week Pearson Correlation .194 1 .375 -.173 Sig. (2-tailed) .413 .103 .466 N 20 20 20 20 Social Support quality Pearson Correlation .530* .375 1 -.318 Sig. (2-tailed) .016 .103 .171 N 20 20 20 20 hrsexer Pearson Correlation -.774** -.173 -.318 1 Sig. (2-tailed) .000 .466 .171 N 20 20 20 20 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). 13. If appropriate, indicate how much variance anxiety 14. Create a table showing the number of married and accounts for in hours worked. If not appropriate, unmarried people in the dataset. Report only the two explain why. correct numbers.</p><p>= number of single: _10___ number of married: __10__ You could calculate r2, but the correlation is not Go to analyze, descriptives, frequencies. significant (p is not below .05), so it is in appropriate to calculate the coefficient of determination (r2).</p><p>15. Create a table to answer this question: What percent hrsexer of people exercise 6 hours or less? Report only the Cumulative Frequency Percent Valid Percent Percent correcxt percent Valid 2 3 15.0 15.0 15.0 4 3 15.0 15.0 30.0 45.0 % 6 3 15.0 15.0 45.0 8 6 30.0 30.0 75.0 10 3 15.0 15.0 90.0 12 2 10.0 10.0 100.0 Go to analyze, descriptives, frequencies, and Total 20 100.0 100.0 use the cumulative percent column. </p><p>16. Correlate anxiety, hours worked, social support, 17. Correlate anxiety, hours worked, social support, and and hours exercised. What’s the strongest observed hours exercised. List all the significant correlations. correlation? [Report symbol and correct value.] [Report symbol and correct value.]</p><p> r = -.7 7 4 Variables: __hrs exerc_ & _anxiety____ r = .5 3 0 r = -.774 = = = =</p><p>18. If appropriate, write the regression equation for 19. If appropriate, predict anxiety given 8 hours of predicting anxiety based on hours of exercise. If not exercise. If not appropriate, explain why. appropriate, explain why. y' 1.507(x)  29.351 y' bx  a y' 1.507(8)  29.351 y' 1.507(x)  29.351 y' 17.295 Coefficientsa</p><p>Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 29.351 2.197 13.361 .000 hrsexer -1.507 .291 -.774 -5.181 .000 a. Dependent Variable: anxiety</p><p>20. If appropriate, write the regression equation for 21. If appropriate, predict anxiety given 6 hours of work. If predicting anxiety based on hours of work. If not not appropriate, explain why. appropriate, explain why.</p><p>Not appropriate, correlation not significant Not appropriate, correlation not significant</p><p>22. Sketch the regression line for predicting anxiety based on hours of exercise. Label appropriately, especially where the y-intercept occurs.</p><p>30</p><p>25 y</p><p> t 20 e i x</p><p> n 15 a</p><p>10</p><p>R Sq Linear = 5 0.599</p><p>2 4 6 8 10 12 hrsexer</p>