Unit VI - guidelines.docx - Data Analysis For each part students have to Repeat the hypothesis H0 and Ha Copy and paste results from running Excel

Unit VI - guidelines.docx - Data Analysis For each part...

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Data Analysis For each part, students have to: - Repeat the hypothesis: H0 and Ha - Copy and paste results from running Excel, highlight R-squared and p-value, and the co-efficient. - Explain p-value: if p-value < .05, therefore, the null hypothesis ( H0 ) is rejected and the alternative hypothesis ( Ha 1 ) is accepted that there is a statistically significant relationship between … - Explain the coefficient: sign and magnitude (level). Show the regression equation - Explain R-squared, which indicate hom many % that the model can explained. Correlation Analysis Hypothesis Testing H0 1 There is no relationship between particulate matter size and employee sick days. HA 1 There is a relationship between particulate matter size and employee sick days. The Pearson correlation coefficient p-value < .05 (alpha), therefore, the null hypothesis ( H0 1 ) is rejected and the alternative hypothesis ( HA 1 ) is accepted that there is a statistically significant relationship between particulate matter size and employee sick days. The Pearson correlation coefficient of r = - 0.715 indicates that particulate matter size, as measured in microns, is strongly and negatively correlated with mean annual sick days per employee. R 2 = .51 indicates that 51 percent of the variability in employee sick days is explained by particulate matter size. micron s mean annual sick days per employee microns 1 mean annual sick days per employee - 0.7159 8 1
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Regression Statistics Multiple R 0.7159841 85 R Square 0.5126333 54 Adjusted R Square 0.5078079 41 Standard Error 1.3277834 55 Observations 103 ANOVA df SS MS F Significan ce F Regression 1 187.29532 39 187.29 53 106.23617 58 1.891E-17 Residual 101 178.06389 94 1.7630 09 Total 102 365.35922 33 Coefficient s Standard Error t Stat P-value Lower 95% Upper 95% Intercept 10.081444 83 0.3151569 69 31.988 65 1.16929E- 54 9.4562582 10.706 63 microns - 0.5223765 54 0.0506812 67 - 10.307 1 1.89059E- 17 -0.622915 - 0.4218 39 Simple Regression Analysis Hypothesis Testing H0 2 There is no relationship between safety training expenditure and lost time hours. HA 2 There is a relationship between safety training expenditure and lost time hours. The safety training expenditure coefficient p-value < .05 (alpha), therefore, the null hypothesis ( H0 2 ) is rejected and the alternative hypothesis ( HA 2 ) is accepted that there is a statistically significant relationship between safety training expenditure and lost time hours.
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The correlation coefficient of r = 0.94 indicates that safety training expenditure is very strongly correlated with lost time hours.
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