Analysis for Corporate Social Performance - Assignment Example

SPSS Exercise ID ID Lecturer You have to use Independent Sample T-Test with for Compare B2B versus B2C as a factor with: a. Social Disclosure Score The average mean for social disclosure in regard to B2C is 52.75 while that related to B2B is 51.90. Group Statistics B2B & B2C N Mean Std. Deviation Std. Error Mean Social Disclosure Score B2C 188 52.75 14.989 1.093 B2B 144 51.90 13.600 1.133 We now check for significance difference in the mean social disclosure between the two groups (B2C and B2B). From the table below, the p-value for Lavene’s test is 0.061 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.591 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no statistically significant difference between the two conditions (B2C and B2B). We can conclude that the differences between condition Means are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Social Disclosure Score Equal variances assumed 3.545 .061 .538 330 .591 .858 1.595 -2.279 3.996 Equal variances not assumed .545 3.21 .586 .858 1.575 -2.239 3.956 b. Employee Turnover %Y The average mean for social disclosure in regard to B2C is 123.59 while that related to B2B is 108.39. Group Statistics B2B & B2C N Mean Std. Deviation Std. Error Mean Employee Turnover %Y B2C 188 123.59 7.584 55.314 B2B 144 108.39 7.132 59.438 We now check for significance difference in the mean social disclosure between the two groups (B2C and B2B). From the table below, the p-value for Lavene’s test is 0.163 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.064 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no statistically significant difference between the two conditions (B2C and B2B). We can conclude that the differences between condition Means (for the employee turnover %) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Employee Turnover %Y Equal variances assumed 1.952 .163 1.857 330 .064 1.52 81.86 -900.81 3.13 Equal variances not assumed 1.872 316 .062 1.52 81.19 -77.26 3.11 c. Community Spend The average mean for social disclosure in regard to B2C is while that related to B2B is . Group Statistics B2B & B2C N Mean Std. Deviation Std. Error Mean Community Spend B2C 188 6.07E9 4.882E10 3.560E9 B2B 144 1.93E11 2.299E12 1.916E11 We now check for significance difference in the mean social disclosure between the two groups (B2C and B2B). From the table below, the p-value for Lavene’s test is 0.026 (a value less than 5% significance level, this means that the variability in the two conditions is different we therefore assume unequal variances and use the p-value assuming equal variances. The p-value is 0.332 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no statistically significant difference between the two conditions (B2C and B2B). We can conclude that the differences between condition Means (for the community spend) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Community Spend Equal variances assumed 4.984 .026 -1.112E0 3.E2 .267 -1.864E11 1.677E11 -5.162E11 1.434E11 Equal variances not assumed -9.729E-1 .332 -1.864E11 1.916E11 -5.652E11 1.924E11 d. Environment discloser score The average mean for social disclosure in regard to B2C is 123.59 while that related to B2B is 108.39. Group Statistics B2B & B2C N Mean Std. Deviation Std. Error Mean Environment Disclosure Score B2C 188 39.23 13.838 1.009 B2B 143 42.07 15.011 1.255 We now check for significance difference in the mean social disclosure between the two groups (B2C and B2B). From the table below, the p-value for Lavene’s test is 0.578 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.076 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no statistically significant difference between the two conditions (B2C and B2B). We can conclude that the differences between condition Means (for the environment disclosure score) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Environment Disclosure Score Equal variances assumed .311 .578 -1.780E0 329 .076 -2.836 1.593 -5.969 .298 Equal variances not assumed -1.761E0 2.922E2 .079 -2.836 1.611 -6.006 .334 e. GHG Emissions: Y The average mean for social disclosure in regard to B2C is 123.59 while that related to B2B is 108.39. Group Statistics B2B & B2C N Mean Std. Deviation Std. Error Mean GHG Emissions: Y B2C 188 2852.22 1.3809E4 1.007E3 B2B 144 9173.65 2.3177E4 1.9314E3 We now check for significance difference in the mean social disclosure between the two groups (B2C and B2B). From the table below, the p-value for Lavene’s test is 0.000 (a value less than 5% significance level, this means that the variability in the two conditions is not the same we therefore assume unequal variances and use the p-value assuming equal variances. The p-value is 0.004 (a value less than 5% significance level), we reject the null hypothesis and conclude that there is evidence of statistically significant difference between the two conditions (B2C and B2B). We can conclude that the differences between condition Means (for the GHG emissions) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper GHG Emissions: Y Equal variances assumed 16.97 .000 -3.092 330 .002 -6.321E3 2.044E3 -1.034E4 -2.30E3 Equal variances not assumed -2.902 219 .004 -6.321E3 2.178E3 -1.061E4 -2.028E3 f. Water Intense/Energy Consumption: Y The average mean for social disclosure in regard to B2C is 123.59 while that related to B2B is 108.39. Group Statistics B2B & B2C N Mean Std. Deviation Std. Error Mean Water Intense/Energy Consumption: Y B2C 188 30848.10 2.0271E5 1.4783E4 B2B 144 16874.38 6.0045E4 5.0038E3 We now check for significance difference in the mean social disclosure between the two groups (B2C and B2B). From the table below, the p-value for Lavene’s test is 0.089 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.424 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no statistically significant difference between the two conditions (B2C and B2B). We can conclude that the differences between condition Means (for the Water Intense/Energy Consumption) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Water Intense/Energy Consumption: Y Equal variances assumed 2.903 .089 .801 3.E2 .424 1.397371629E4 1.745588248E4 -2.036512348E4 4.831255606E4 Equal variances not assumed .895 .372 1.397371629E4 1.560769605E4 -1.677977769E4 4.472721026E4 2- You have to use here One-Way ANOVA to compare Country (Continent) with: a. Social Disclosure Score In this part, we check if the condition means are relatively the same or if they are significantly different from one another. We use the p-values (sig.) to check on this condition. From the table below, we observe that the p-value is 0.014 (a value less than 5% significance level), we therefore reject the null hypothesis and conclude that the social disclosure score is different across the countries (continent). ANOVA Social Disclosure Score Sum of Squares df Mean Square F Sig. Between Groups 2571.643 4 642.911 3.188 .014 Within Groups 65950.983 327 201.685 Total 68522.627 331 b. Employee Turnover %Y In this part, we check if the condition means (for the employee turnover %) are relatively the same or if they are significantly different from one another. We use the p-values (sig.) to check on this condition. From the table below, we observe that the p-value is 0.732 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the employee turnover % is not different across the countries (continent). ANOVA Employee Turnover %Y Sum of Squares df Mean Square F Sig. Between Groups 111.838 4 27.960 .505 .732 Within Groups 18107.795 327 55.376 Total 18219.634 331 c. Community Spend In this part, we check if the condition means (for the community spend) are relatively the same or if they are significantly different from one another. We use the p-values (sig.) to check on this condition. From the table below, we observe that the p-value is 0.526 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the community spend is not different across the countries (continent). ANOVA Community Spend Sum of Squares df Mean Square F Sig. Between Groups 7.355E24 4 1.839E24 .800 .526 Within Groups 7.518E26 327 2.299E24 Total 7.592E26 331 d. Environment discloser score In this part, we check if the condition means (for the employee turnover %) are relatively the same or if they are significantly different from one another. We use the p-values (sig.) to check on this condition. From the table below, we observe that the p-value is 0.732 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the employee turnover % is not different across the countries (continent). ANOVA Environment Disclosure Score Sum of Squares df Mean Square F Sig. Between Groups 1650.178 4 412.545 2.013 .092 Within Groups 66806.021 326 204.926 Total 68456.199 330 e. GHG Emissions: Y In this part, we check if the condition means (for the GHG Emissions) are relatively the same or if they are significantly different from one another. We use the p-values (sig.) to check on this condition. From the table below, we observe that the p-value is 0.011 (a value less than 5% significance level), we therefore reject the null hypothesis and conclude that the GHG emissions is different across the countries (continent). ANOVA GHG Emissions: Y Sum of Squares df Mean Square F Sig. Between Groups 4.529E9 4 1.132E9 3.329 .011 Within Groups 1.112E11 327 3.401E8 Total 1.157E11 331 f. Water Intense/Energy Consumption: Y In this part, we check if the condition means (for the water intense/energy consumption) are relatively the same or if they are significantly different from one another. We use the p-values (sig.) to check on this condition. From the table below, we observe that the p-value is 0.640 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the water intense/energy consumption is not different across the countries (continent). ANOVA Water Intense/Energy Consumption: Y Sum of Squares df Mean Square F Sig. Between Groups 6.302E10 4 1.576E10 .632 .640 Within Groups 8.152E12 327 2.493E10 Total 8.215E12 331 3- Compare Average Return: Y-1 with: a. Social Disclosure Score The average mean for social disclosure in regard to High is 52.68 while that related to low is 51.62. Group Statistics Average Return N Mean Std. Deviation Std. Error Mean Social Disclosure Score Low 93 51.62 13.787 1.430 High 239 52.68 14.633 .947 We now check for significance difference in the mean social disclosure between the two groups (High and Low). From the table below, the p-value for Lavene’s test is 0.385 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.547 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no statistically significant difference between the two conditions (High and Low). We can conclude that the differences between condition Means (for the social disclosure score) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Social Disclosure Score Equal variances assumed .756 .385 -0.603 330 .547 -1.061 1.760 -4.524 2.401 Equal variances not assumed -0.619 177 .537 -1.061 1.715 -4.445 2.323 b. Employee Turnover %Y The average mean for social disclosure in regard to Low is 13.068 while that related to High is 11.167. Group Statistics Average Return N Mean Std. Deviation Std. Error Mean Employee Turnover %Y Low 93 13.068 7.4745 0.77507 High 239 11.167 7.344 0.47507 We now check for significance difference in the mean social disclosure between the two groups (High and Low). From the table below, the p-value for Lavene’s test is 0.713 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.036 (a value less than 5% significance level), we reject the null hypothesis and conclude that there is evidence of statistically significant difference between the two conditions (High and Low). We can conclude that the differences between condition Means (for the employees) are likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Employee Turnover %Y Equal variances assumed .136 .713 2.107 330 .036 1.901 -0.902 -0.126 3.676 Equal variances not assumed 2.091 165 .038 1.901 -0.909 -0.106 3.696 c. Community Spend The average mean for social disclosure in regard to High is while that related to low is . Group Statistics Average Return N Mean Std. Deviation Std. Error Mean Community Spend Low 93 4.99E8 3.001E9 3.112E8 High 239 1.21E11 1.785E12 1.155E11 We now check for significance difference in the mean social disclosure between the two groups (High and Low). From the table below, the p-value for Lavene’s test is 0.202 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.517 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no evidence of statistically significant difference between the two conditions (High and Low). We can conclude that the differences between condition Means (for the community spend) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Community Spend Equal variances assumed 1.635 .202 -0.648 330 .517 -1.201E11 1.853E11 -4.845E11 2.444E11 Equal variances not assumed -1.040 238 .299 -1.201E11 1.155E11 -3.475E11 1.074E11 d. Environment discloser score The average mean for social disclosure in regard to Low is 39.83 while that related to High is 40.71 Group Statistics Average Return N Mean Std. Deviation Std. Error Mean Environment Disclosure Score Low 93 39.83 13.055 1.354 High 238 40.71 14.915 .967 We now check for significance difference in the mean social disclosure between the two groups (High and Low). From the table below, the p-value for Lavene’s test is 0.204 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.619 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no evidence of statistically significant difference between the two conditions (High and Low). We can conclude that the differences between condition Means (for the environment disclosure score) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Environment Disclosure Score Equal variances assumed 1.621 .204 -0.4979 329 .619 -.878 1.763 -4.347 2.591 Equal variances not assumed -0.5278 191 .598 -.878 1.664 -4.159 2.403 e. GHG Emissions: Y The average mean for social disclosure in regard to Low is 6091.3 while that related to High is 5400.58. Group Statistics Average Return N Mean Std. Deviation Std. Error Mean GHG Emissions: Y Low 93 6091.23 18165.983 1883.725 High 239 5400.579 18936.258 1224.885 We now check for significance difference in the mean social disclosure between the two groups (High and Low). From the table below, the p-value for Lavene’s test is 0.536 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.763 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no evidence of statistically significant difference between the two conditions (High and Low). We can conclude that the differences between condition Means (for the GHG emissions) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper GHG Emissions: Y Equal variances assumed .383 .536 .302 330 .763 690.655 2288.460 -3811.156 5192.46 Equal variances not assumed .307 174 .759 690.655 22469.449 -3744.084 5125.39 f. Water Intense/Energy Consumption: Y The average mean for social disclosure in regard to Low is 6091.3 while that related to High is 5400.58. Group Statistics Average Return N Mean Std. Deviation Std. Error Mean Water Intense/Energy Consumption: Y Low 93 27087.36 147328.43 15277.25 High 239 23892.18 161631.32 10455.06 We now check for significance difference in the mean social disclosure between the two groups (High and Low). From the table below, the p-value for Lavene’s test is 0.887 (a value greater than 5% significance level, this means that the variability in the two conditions is about the same we therefore assume equal variances and use the p-value assuming equal variances. The p-value is 0.868 (a value greater than 5% significance level), we fail to reject the null hypothesis and conclude that there is no evidence of statistically significant difference between the two conditions (High and Low). We can conclude that the differences between condition Means (for the Water Intense/Energy Consumption) are likely due to chance and not likely due to the independent variable manipulation. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Water Intense/Energy Consumption: Y Equal variances assumed .020 .887 .166 330 .868 3195.19 1.928E4 -3.474E4 4.113E4 Equal variances not assumed .173 182.9 .863 3195.19 1.851E4 -3.332E4 3.972E4 . 4- Compare GICS Industry Name with: a. Social Disclosure Score The p-value helps to determine if the condition means are relatively the same or if they are significantly different from one another. From the table below, we observe that the p-value is 0.186 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the social disclosure score is not different across the different GICS Industries. ANOVA Social Disclosure Score Sum of Squares df Mean Square F Sig. Between Groups 11142.314 46 242.224 1.203 .186 Within Groups 57380.312 285 201.334 Total 68522.627 331 b. Employee Turnover %Y The p-value helps to determine if the condition means are relatively the same or if they are significantly different from one another. From the table below, we observe that the p-value is 0.277 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the employee turnover % (Y) is not different across the different GICS Industries. ANOVA Employee Turnover %Y Sum of Squares df Mean Square F Sig. Between Groups 2804.287 46 60.963 1.127 .277 Within Groups 15415.346 285 54.089 Total 18219.634 331 c. Community Spend The p-value helps to determine if the condition means are relatively the same or if they are significantly different from one another. From the table below, we observe that the p-value is 0.384 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the community spend is not different across the different GICS Industries. ANOVA Community Spend Sum of Squares df Mean Square F Sig. Between Groups 1.105E26 46 2.402E24 1.056 .384 Within Groups 6.487E26 285 2.276E24 Total 7.592E26 331 d. Environment discloser score The p-value helps to determine if the condition means are relatively the same or if they are significantly different from one another. From the table below, we observe that the p-value is 0.201 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the environment disclosure score is not different across the different GICS Industries. ANOVA Environment Disclosure Score Sum of Squares df Mean Square F Sig. Between Groups 11054.665 46 240.319 1.189 .201 Within Groups 57401.535 284 202.118 Total 68456.199 330 e. GHG Emissions: Y The p-value helps to determine if the condition means are relatively the same or if they are significantly different from one another. From the table below, we observe that the p-value is 0.000 (a value less than 5% significance level), we therefore reject the null hypothesis and conclude that the GHG Emissions is different across the different GICS Industries. ANOVA GHG Emissions: Y Sum of Squares df Mean Square F Sig. Between Groups 3.176E10 46 6.905E8 2.343 .000 Within Groups 8.397E10 285 2.946E8 Total 1.157E11 331 f. Water Intense/Energy Consumption: Y The p-value helps to determine if the condition means are relatively the same or if they are significantly different from one another. From the table below, we observe that the p-value is 0.998 (a value greater than 5% significance level), we therefore fail to reject the null hypothesis and conclude that the water intense/energy consumption is not different across the different GICS Industries. ANOVA Water Intense/Energy Consumption: Y Sum of Squares df Mean Square F Sig. Between Groups 6.029E11 46 1.311E10 .491 .998 Within Groups 7.612E12 285 2.671E10 Total 8.215E12 331 Read More