43 college students
44% male, 56% female
Students reported on the number of hours spent studying per week (0-40 hours), their life satisfaction (scale from 0-100), degree of stress they experienced over the last month (scale 0-5), and completed an IQ test (40-160).
Students also reported their gender (1=male, 2=female) and cumulative GPA.
For the statistical analysis performed, you need to provide responses to two questions:
SPSS Output: Statistical Analysis 1
|
Variables Entered/Removedb |
|||
|
Model |
Variables Entered |
Variables Removed |
Method |
|
1 |
stress, IQ, hrsstudy, Gender, gpa |
. |
Enter |
|
a. All requested variables entered. b. Dependent Variable: lifesatisfaction |
|||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
|
1 |
.770a |
.593 |
.541 |
11.618 |
|
ANOVAb |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
7672.577 |
5 |
1534.515 |
11.368 |
.000a |
|
Residual |
5264.223 |
39 |
134.980 |
|||
|
Total |
12936.800 |
44 |
||||
|
a. Predictors: (Constant), stress, IQ, hrsstudy, Gender, gpa b. Dependent Variable: lifesatisfaction |
||||||
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
49.710 |
15.314 |
3.246 |
.002 |
|
|
Gender |
-.985 |
3.966 |
-.029 |
-.248 |
.805 |
|
|
gpa |
10.921 |
3.686 |
.453 |
2.963 |
.005 |
|
|
IQ |
.151 |
.178 |
.114 |
.853 |
.399 |
|
|
hrsstudy |
-.088 |
.400 |
-.024 |
-.221 |
.826 |
|
|
stress |
-5.519 |
1.667 |
-.406 |
-3.310 |
.002 |
|
|
a. Dependent Variable: lifesatisfaction |
||||||
We need at least 10 more requests to produce the answer.
0 / 10 have requested this problem solution
The more requests, the faster the answer.
43 college students 44% male, 56% female Students reported on the number of hours spent studying...
43 college students 44% male, 56% female Students reported on the number of hours spent studying per week (0-40 hours), their life satisfaction (scale from 0-100), degree of stress they experienced over the last month (scale 0-5), and completed an IQ test (40-160). Students also reported their gender (1=male, 2=female) and cumulative GPA. For the statistical analysis performed, you need to provide responses to two questions: What type of statistical analysis was used to examine what kind of research question?...
Overview of the Study: The data are based on a Comprehensive School Reform (CSR) Initiative that focused on the improvement of reading and writing for students in the primary grade. The school received a grant from the state which was used to strengthen classroom teachers’ instructional skills. The regression outputs present information for students in the school. Description of the variables: Please use the following description/coding to help you in your analyses. Gender: female; 1 male=0 Coding – Gender female...
Models 1-7 are below
Part C: Select one model you would use to explain reading ability.,Then use that model to find the 95% confidence interval estimate for the mean reading ability 95% prediction interval for reading ability When age 6, mem span 4.2 and ig 91. Regression [DataSetll C:\Usersn.little5773 Downloads\child data.sav Variables Entered/Removed Variables Entered Variables Removed Method Model Enter age a. Dependent Variable: reading ability b. All requested variables entered. Model Summary Adjusted R Square Std. Error o R...
Overview of the Study: The data are based on a Comprehensive School Reform (CSR) Initiative that focused on the improvement of reading and writing for students in the primary grade. The school received a grant from the state which was used to strengthen classroom teachers’ instructional skills. The regression outputs present information for students in the school. Description of the variables: Please use the following description/coding to help you in your analyses. Gender: female; 1 male=0 Coding – Gender female...
From the three three Regression tests, come up with three
hypotheses.
Regression Method Variables Entered/Removeda Variables Model Variables Entered Removed 1 TotElectb a. Dependent Variable: Variety Seeking b. All requested variables entered. Enter Model Summary Adjusted R R Square Square .009 .002 Model R Std. Error of the Estimate .64205 1 .0958 a. Predictors: (Constant), TotElect Coefficients a Standardized Coefficients Model Unstandardized Coefficients B Std. Error 3.667 . 108 Beta t Sig. .000 1 (Constant) 34.075 TotElect .008 .007 .095...
A researcher uses two
regression models to seek answers to two research questions. These
models are:
Y1 = Bo1 + B11X1
Y2 = Bo2 + B12X1 + B22X12
Test the null hypotheses for both models. Use the results of
your analyses to recommend an appropriate model. In each of the
above two cases, state your null and alternative hypotheses,
decision criteria, decision and conclusion.
The level of significance is 5%. The data for this study are
presented in the table...
n Grade, Number of Hours they Spent Studying, Major, Gender, and ation in panal tGPA for a Random Sample of 17 Students Hours Studying Major Gender Current GPA 3.41 2.98 2.64 3.12 3.68 3.45 3.8 1.87 2.74 10 Business Engineering and science Liberal arts Liberal arts Liberal arts Engineering and science Male Male Female Male Female Female Male 12 14 Business Engineering and science Liberal arts Business Business Liberal arts Liberal arts Engineering and science Engineering and science Liberal arts...
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admissions department of a small liberal arts college. You wonder if you can predict students' college grade point averages (GPAs) by their SAT scores. You randomly select 50 recent graduates and collect their SAT scores and college GPAs. You use a statistical software package to run a regression predicting college GPA from SAT score. Use the following output to answer the questions that follovw Descriptive Statistics...
Below are the results of two regressions. The first is to predict the number of low-income families in a state based on the number of people in the labor force. The second is to predict the number of low- income families in a state based on the number of people in the labor force and the average years of school of the citizens: 1 Adjusted R Std. Error of Model R R Square Square the Estimate .270a .073 .052 38.84010...
With each hybrid automobile model, prepare a summary that does the following: 2. Interprets the directional of the relationship of each statistically significant independent variable with respect to the preference for the hybrid model concerned. relative importance of each of the stalisticu idependent variables. 4. Assesses the strength of the statistically significant independent variables as they join to predict the preferences for the hybrid model concerned. Coefficients Model Unstandardized Coefficients Sig Standardized Coefficients t Std. Error Beta 6.981 13.795 .000...