SPSS Statistics XXXXXXXXXXRegression Satinst: This variable measures the average level of satisfaction with the undergraduate educational experience for the students within institutions. That is, each...

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SPSS Statistics Regression Satinst: This variable measures the average level of satisfaction with the undergraduate educational experience for the students within institutions. That is, each student reported their level of satisfaction, and this variable is the average response of students at each institution. Higher values indicate that the student body has higher levels of satisfaction with their educational experience (alternatively, one could interpret this as the level of satisfaction for the “average” student within the institutions). Control: This variable represents whether the institution is a public or private institution. It is coded such that 1 = public and 2 = private. Select: This variable is a measure of the selectivity of the institution as measured by the average ACT or SAT equivalent score for entering freshmen. Size: This variable is an indicator of the size of the institution as measured by the number of full-time equivalent students within the institution. Chgthink: Four years after enrollment, each student within institutions indicated the extent to which their critical thinking abilities had changed as a result of attending the institution. This variable is the average response of the students within each institution. Higher values indicate that the student body (or “average” student) perceives more change in critical thinking abilities. Chggen: Four years after enrollment, each student within institutions indicated the extent to which their general knowledgehad changed as a result of attending the institution. This variable is the average response of the students within each institution. Higher values indicate that the student body (or “average” student) perceives more change in their general knowledge. Chgfield: Four years after enrollment, each student within institutions indicated the extent to which their knowledge of a particular field had changed as a result of attending the institution (one would certainly hope that students perceived good gains in this area, as it is talking about their major). This variable is the average response of the students within each institution. Higher values indicate that the student body (or “average” student) perceives more change in knowledge of a particular field. E. Conduct an analysis that answers two questions: (1) are structural characteristics of institutions (control, selectivity, size) or characteristics of the student bodies (chgthink, chggen, chgfield)more important in explaining the variance in the overall satisfaction with the institution of the student bodies? and (2) considering these six characteristics, which have a unique relationship to institutional satisfaction? To do a block-entry, hierarchical analysis of these data, with satinst as the dependent variable, you should first enter the structural characteristics as model 1. These characteristics exist at students’ entry into the institutions. Four years after entry, students responded to questions about their growth and development as a result of attending that institution. Thus, we have a temporal argument for adding the three characteristics of the student bodies in model 2. Model 1 will have 3 independent variables (structural characteristics) and Model 2 will have 6 independent variables (structural and student body characteristics). Use the output from this analysis with α = .05 to answer the following questions: 1.(a)What proportion of variance in satisfaction with the institution is explained by the structural characteristics alone? (b) Is the variance explained significantly different from 0? What was the F value and accompanying significance value? 2.(a) What proportion of variance in satisfaction with the institution is explained by thecharacteristics of the student body over and beyond that explained by structural characteristics? (b) Is the variance explained significantly different from 0? What was the F value and accompanying significance value? 3.(a) What is the total variance explained by the set of six independent variables? (b) Is this variance explained significantly different from 0? What was the F value and accompanying significance value? 4.Does multicollinearity appear to be a problem in this analysis? Why or why not? 5.In the full model (Model 2), which of the independent variables have a significant unique relationship to satisfaction with the institution? What did you use to determine your answer? 6.What is the relative importance of the independent variables in their influences on satisfaction? What did you use to determine your answer? 7.In the full model (Model 2), how do you interpret the coefficient for control? 8.Some researchers argue that structural characteristics of institutions are not important with respect to students’ satisfaction with their undergraduate educational experience. Would you agree or disagree with this argument, and on what basis? 9.Write a results section describing the findings of this study based on the analyses you have completed .F.Turn in your answers along with your SPSS output(you do NOT need to include any descriptive statistics). Be sure to annotate your SPSS output, indicating where you obtained the information for your answers ANCOVA A researcher is conducting a study of the differential effectiveness of three methods of reading instruction. She randomly assigns 120 students to one of the three methods. She realizes that learning to read is correlated with intelligence and since at the end of the previous school year all students were administered an IQ test, she decides to use IQ scores as a covariate. You are to use this data to help this researcher conduct an analysis of covariance. Be sure to discuss the following in your report of the analysis: 1.Is the independent variable (reading method) related to reading achievement test scores (RAchv2)? 2.Use appropriate follow-up tests for ANCOVA to identify which adjusted means have statistically significant differences. 3.Are the results any different than what would have been discovered with a one-way analysis of variance(you will need to run a one-way ANOVA to determine this)? 4.Do the assumptions for ANCOVA appear to be reasonable in this situation? Why? 5.Does this appear to be an appropriate use of a covariate? Why? What is the correlation between the covariate and the dependent variable?
Answered 1 days AfterApr 20, 2021

Answer To: SPSS Statistics XXXXXXXXXXRegression Satinst: This variable measures the average level of...

Anu answered on Apr 21 2021
117 Votes
1.(a)    What proportion of variance in satisfaction with the institution is explained by the structural characteristics alone?
Ans.    Following table represent the model summary of SPSS when we did the regression by taking satisfaction as dependent variable and structural characteristics as independent variable
. From this table we can see that the value of R square is 0.089 that means structural characteristics alone explain the 8% variation in satisfaction.
    Model Summary
    Model
    R
    R Square
    Adjusted R Square
    Std. Error of the Estimate
    1
    .299a
    .089
    .080
    .76550
    a. Predictors: (Constant), size, select, control
(b)     Is the variance explained significantly different from 0? What was the F value and accompanying significance value?
Ans.    Yes the variance explained is significantly different from zero. F(3,283) = 9.270, p-value = 0.000 < 0.05 shows that the predictors significantly predict the dependent variable.
    ANOVAb
    Model
    Sum of Squares
    df
    Mean Square
    F
    Sig.
    1
    Regression
    16.297
    3
    5.432
    9.270
    .000a
    
    Residual
    165.836
    283
    .586
    
    
    
    Total
    182.134
    286
    
    
    
    a. Predictors: (Constant), size, select, control
    
    
    
    b. Dependent Variable: satinst
    
    
    
    
2.    (a) What proportion of variance in satisfaction with the institution is explained by the characteristics of the student body over and beyond that explained by structural characteristics?
Ans.    Following table represent the model summary of SPSS when we did the regression by taking satisfaction as dependent variable and characteristics of student body as independent variable. From this table we can see that the value of R square is 0.180 that means structural characteristics alone explain the 18% variation in satisfaction.
    Model Summary
    Model
    R
    R Square
    Adjusted R Square
    Std. Error of the Estimate
    1
    .424a
    .180
    .171
    .72355
    a. Predictors: (Constant), chgfield, chgthink, chggen
(b) Is the variance explained significantly different from 0? What was the F value and accompanying significance value?
Ans.    Yes the variance explained is significantly different from zero. F(3,283) = 20.586, p-value = 0.000 < 0.05 shows that the predictors significantly predict the dependent variable.
    ANOVAb
    Model
    Sum of Squares
    df
    Mean Square
    F
    Sig.
    1
    Regression
    32.332
    3
    10.777
    20.586
    .000a
    
    Residual
    147.636
    282
    .524
    
    
    
    Total
    179.968
    285
    
    
    
    a. Predictors: (Constant), chgfield, chgthink, chggen
    
    
    b. Dependent Variable: satinst
    
    
    
    
3.(a)     What is the total variance explained by the set of six independent variables?
Ans.    Following table represent the model summary of SPSS when we did the regression by taking satisfaction as dependent variable and chgfield, size, select, chggen, chgthink and control as independent variable. From this table we can see that the value of R square is 0.254 that means structural characteristics alone explain the 25.4% variation in satisfaction.
    Model Summary
    Model
    R
    R Square
    Adjusted R Square
    Std. Error of the...
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