Problem 2 A mental health agency measured the self-esteem score for randomly selected individuals with disabilities who were involved in some work activity within the past year. The spreadsheet named Self Esteem provides the data including each individuals self-esteem measure {y}, years of education [YrsEdu}, age, days worked in the last year [DayWork}, marital status dummy variables {MS-2, M33, M54} indicating if the individual is single, married, separated, or divorced, and a support level {SL} dummy variable indicating if' the level of'job support (counseling, etc) was provided directly (I) or indirectly {13'} Regarding marital status, if' single all MS indicators are I], while M32 = ] indicates married, M53 = 1 indicates separated, and M54 = 1 indicates divorced. a. {4 points] In cell N4, use Excel's \"Correlation" Data Analysis tool to construct a correlation matrix for all the variables. Note that the categories in columns I and .l should not be included since the data are already represented as dummy variables in columns E through H. b. [6 points} Considering the correlation between self'esteem and each 3: variable, identify the three variables that, based on correlation with 3.? alone, should be considered as best candidates for inclusion in the model. Shade the appropriate cells containing the correlation values in yellow. Ignore any multicollinearity concerns for this part. c. {6 points} Considering the correlation between each pair of 1: variables, identify the variables that would possibly cause multicollinearityr problems if included in the model. Shade the appropriate cells containing the correlation values in green. d. {4 points] Based on your conclusions in parts b and c, shade in red color the names of any variables that should NOT be included in the initial model because of possible multicollinearity problems. e. {4 points} With cell N16 as the upper left corner of'the output, use Excel Data Analysis tool to generate the full regression model {include all 1: variables}. [Do not generate the residual plot.] 1". {6 points} Considering the regression output from part e, shade in yellow the name of' any 3: variable that appears significant and should remain in the model. Also shade the corresponding r star and pvalue. Consider the p-value small if it is less than . g. {4 points} Partial Regression Model: With cell N43 as the upper left corner of the output, use Excel Data Analysis tool to generate the regression model including only the x variable[s) that were found to be signicant in part 1". [Do not generate the residual plot.) IKI LIl'vll 1| A | 3 l c: | D | E | F | G |H| I | J E 1' X2 X3 )(1 X4 X5 XE x7 CategoricalVariables YrsEdu Age DavWark M52 M53 M54 51 51 MS 3 2 9 52 4 O D 0 0 None Single 5 11 4-0 14- 0 D 0 1 Direct Single in 9 1D 1 Direct Single 3" 12 12 O D 0 0 None Single 9 1D 50 O D 0 0 None Single 13 1o 44 0 None Single 3 9 4-5 9 1 D 0 1 Direct Married 12 5 4? n- 0 None Married E 10 51 1 D 0 0 None Married 14 5 4? 11 1 Direct Separated E 9 51 10 O 1 0 1 Direct Separated 16 1o 42 12 1 Direct Separated 1? 9 4-8 9 O 1 0 1 Direct Separated 13 E 5 46 3 0 None Separated E 12 3? 14- 0 1 0 0 None Separated 2D 12 35 13 0 None Separated A 9 4-3 3 O 1 0 0 None Separated 22 1o 45 4 0 None Separated a 10 50 10 O D 1 1 Direct Divorced 24 5 46 n- 0 None Divorced E 11 4-9 0 D 1 0 None Divorced 26 12 43 0 None Divorced 2? 10 4-5 8 O D 1 0 None Divorced 23 5 4? E- 0 None Divorced a 9 4-5 0 D 1 0 None Divorced 3D 9 4? n- 0 None Divorced i 10 4-5 0 D 1 0 None Divorced 32 1o 4? 0 None Divorced i 13 23 12 o o o 1 Direct Single 34 12 42 3? 1 Direct Single E 10 4-0 23 O D 0 1 Direct Single m 12 33 23 1 Direct Single 3 9 4-5 10 O 0 O 1 Direct Single n 10 4? 1o 1 Direct Single _ 9 4? 9 O 0 O 1 Direct Single m 12 39 23 0 None Married 3 10 4-3 12 O 1 O 1 Direct Separated 42 11 39 21 0 None Separated E 12 33 10 O 1 O 0 None Separated 44 12 35 11 0 None Separated E 12 4-5 14- 0 0 1 0 None Divorced m 13 41 12 0 None Divorced 4? 9 4-3 5 O 0 1 0 None Divorced 43 12 23 51 1 Direct Single L 4- 32 4-0 0 0 O 1 Direct Single 5D 14 33 29 1 Direct Single 3 4- 35 29 O 0 O 1 Direct Single 52 14 39 29 1 Direct Single i 3 39 21 O 0 O 1 Direct Single 54 9 43 ? 1 Direct Married E 2 29 24- 1 0 O 1 Direct Married 56 13 26 32 1 Direct Married 5? 4- 30 37" O 1 0 1 Direct Separated 53 13 26 31 1 Direct Divorced 2 2? 58 O 0 0 1 Direct Single 643 12 33 1? 0 None Single i 5 28 51 1 0 0 1 Direct Married 62 E 14- 38 E4- 0 1 0 1 Direct Separated E 64 N | u estiorls 2a2d Questions 2e, 2f u estion 2g