SPSS: Week 9 Imagine a researcher is interested in examining the relationship of self-esteem (ScoreOne) and productivity (ProdOne). The researcher is also interested in the ability to predict the productivity of teachers using years of teaching (Experience) as the predicting variable. Use the teachersurvey.sav data set to conduct the analysis involving ScoreOne, ProdOne, and Experience. Use these data to answer the questions below (these data have already been entered in a SPSS file; see the note below the data table). Gender (M = male, F = female) M M F M F F F F M M F F F F M M F M F M M M F F M F M M F M Self-esteem scores 64 68 74 75 76 79 80 82 68 70 74 76 78 79 82 85 71 73 75 77 78 80 83 86 73 74 77 77 78 81 Productivity scores 25 28 36 38 34 36 40 41 22 38 39 34 38 37 45 46 30 34 33 36 38 42 46 49 37 38 32 35 36 45 F F F M F F M M F F 84 87 77 71 75 76 79 83 89 91 49 48 36 33 34 36 38 48 48 49 Download the SPSS data set: teachersurvey.sav. Not all of the variables in that SPSS file will be used for this assignment. 2. Produce an SPSS output for an analysis of regression examining the impact of participants' years of Experience on their productivity. Variables Entered/Removeda Model 1 Variables Variables Entered Removed ProdOneb Method . Enter a. Dependent Variable: Experience b. All requested variables entered. Model Summary Model R .116a 1 R Square Adjusted R Std. Error of the Square Estimate .014 -.012 8.045 a. Predictors: (Constant), ProdOne ANOVAa Model Sum of Squares Regression 1 df Mean Square 33.813 1 33.813 Residual 2459.162 38 64.715 Total 2492.975 39 F Sig. .522 .474b a. Dependent Variable: Experience b. Predictors: (Constant), ProdOne Coefficientsa Model Unstandardized Coefficients Standardized t Sig. Coefficients B 1 (Constant) ProdOne Std. Error 21.422 7.574 -.141 .196 Beta -.116 2.828 .007 -.723 .474 a. Dependent Variable: Experience D) What can be concluded from these results? Be sure to consider possible study limitations and recommendations for future research. E.) Given only two variables were examined, how does testing the significance of the regression equation relate to testing the significance of the Pearson correlation