CHYS 3P15 Winter 2023: Assignment 4 Instructions and Submission Checklist: • Please use Assignment 4 Dataset • Your assignment write up (i

CHYS 3P15 Winter 2023: Assignment 4

Instructions and Submission Checklist:

• Please use Assignment 4 Dataset

• Your assignment write up (i.e., double spaced word document) in APA format on a

separate page (82 marks total)

• Your annotated syntax file uploaded onto Sakai (10 marks- Questions 1 and 2)

o Please include all syntax used in your assignment (i.e., if you made any errors or

re-ran analyses, please delete irrelevant syntax so that TAs do not have to

“search” for the correct version)

o If it is unclear, a mark of 0 will be given.

• Your output file uploaded onto Sakai as PDF (10 marks- Questions 1 and 2)

o Please include all output used in your assignment (i.e., if you made any errors or

re-ran analyses, please delete irrelevant output so that TAs do not have to

“search” for the correct version)

o If it is unclear, a mark of 0 will be given.

• APA style formatting for writing and tables (5 marks for writing, 5 marks for tables = 10 marks)

Multiple Regression Analyses

Using multiple regression analyses, test the following hypotheses:

1. Participant sex and completing a study program or not will predict grade in writing grade

(32 marks)

2. Participant number of hours studying, math grade, and reading grade will predict writing

grade after accounting for the effects of participant sex and study program in step 1

(hierarchical multiple regression- interpret Model 2 only). (50 marks; 4 marks for type of

test and hypotheses, 42 marks for Model 2)

Helpful Hints: J

o Your write up should be formal and reflect what you would see in an APA

formatted results section of a published journal article:

§ State research question and test used

§ N sample size

§ State null and alternate hypothesis

§ State F statement and interpretation

§ State R2 and interpretation

§ State R2 change and interpretation (for hierarchical)

§ Predictors b, se, beta, and p (at step they were entered unless otherwise

asked)

§ Interpret as significant or not, if significant interpret b

§ Regression table (and include sr2

- only for significant predictors)

§ Report M and SD of all variables

§ Report bivariate correlations of all variables

o Recall that each block or model has its own F statement, R2 (and R2 change when

applicable). Refer to the question to see which block should be reported.

o Each predictor should have its own b, se, beta, p value and squared semipartial

correlation (unique variance; sr2

).

o Your report should include 2 APA formatted tables; a table with

correlation/means/standard deviations for all variables in this assignment, and 1

multiple regression table (Questions 1 and 2 can be entered as 2 steps in a single

table).

o If results are in a table, please refer to the table for the statistics/values BUT

interpret them in text (i.e., how you knew predictor was or was not significant),

and the direction of coefficients (e.g., “for every unit increase…”)

o Even if predictors are not significant, their b, se, beta and p values should be in

the regression table.

o When in doubt, consult APA manual for more details, lecture notes, and Sakai

handouts

**You do NOT need to report assumptions for this assignment**

Regression Notes Output Created Comments Input Data Active Dataset Filter Weight Split File N of Rows in Working Data File Missing Value Handling Definition of Missing Cases Used Syntax Resources Processor Time Elapsed Time Memory Required Additional Memory Required for Residual Plots 04-APR-2023 16:02:10 /Users/tyessacameron/D ownloads/CHYS 3P15 Assignment 4 Dataset. sav DataSet1 100 User-defined missing values are treated as missing. Statistics are based on cases with no missing values for any variable used. REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA CHANGE ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT writing /METHOD=ENTER Sex Program. 00:00:00.04 00:00:00.00 3056 bytes 0 bytes [DataSet1] /Users/tyessacameron/Downloads/CHYS 3P15 Assignment 4 Dataset.sav Page 1 Descriptive Statistics Mean Std. Deviation N Grade in writing in percent Participant sex at birth whether or not participants completed a study program 68.63 16.418 100 .4700 .50161 100 .3400 .47610 100 Correlations Grade in writing in percent Participant sex at birth whether or not participants completed a study program Pearson Correlation Grade in writing in percent Participant sex at birth whether or not participants completed a study program Sig. (1-tailed) Grade in writing in percent Participant sex at birth whether or not participants completed a study program N Grade in writing in percent Participant sex at birth whether or not participants completed a study program 1.000 .433 .232 .433 1.000 -.041 .232 -.041 1.000 . <.001 .010 .000 . .341 .010 .341 . 100 100 100 100 100 100 100 100 100 Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 whether or not participants completed a study program, Participant sex at birthb . Enter Dependent Variable: Grade in writing in percent a. b. All requested variables entered. Page 2 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 1 .500a .250 .235 14.359 .250 16.209 2 9 7 Model Summary Model Change Statistics df2 Sig. F Change 1 9 7 ><.001 a. Predictors: (Constant), whether or not participants completed a study program, Participant sex at birth ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression Residual Total 6684.554 2 3342.277 16.209 ><.001 b 20000.756 9 7 206.193 26685.310 9 9 a. Dependent Variable: Grade in writing in percent Predictors: (Constant), whether or not participants completed a study program, Participant sex at birth b. Coefficientsa Model Unstandardized Coefficients Standardized Coefficients B Std. Error Beta t 1 (Constant) Participant sex at birth whether or not participants completed a study program 58.866 2.252 26.135 ><.001 14.526 2.880 .444 5.045 ><.001 8.637 3.034 .250 2.847 .005 Coefficientsa Model Sig. Correlations Zero-order Partial Part 1 (Constant) Participant sex at birth whether or not participants completed a study program ><.001 ><.001 .433 .456 .443 .005 .232 .278 .250 a. Dependent Variable: Grade in writing in percent Page 3 Regression Notes Output Created Comments Input Data Active Dataset Filter Weight Split File N of Rows in Working Data File Missing Value Handling Definition of Missing Cases Used Syntax Resources Processor Time Elapsed Time Memory Required Additional Memory Required for Residual Plots 04-APR-2023 23:44:19 /Users/tyessacameron/D ownloads/CHYS 3P15 Assignment 4 Dataset. sav DataSet1 >100 User-defined missing values are treated as missing. Statistics are based on cases with no missing values for any variable used. REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA CHANGE ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT writing /METHOD=ENTER Study math reading Sex /METHOD=ENTER Program. 00:00:00.06 00:00:00.00 4928 bytes 0 bytes [DataSet1] /Users/tyessacameron/Downloads/CHYS 3P15 Assignment 4 Dataset.sav Page 4 Descriptive Statistics Mean Std. Deviation N Grade in writing in percent Number of hours studying per week Grade in math in percent Grade in reading in percent Participant sex at birth whether or not participants completed a study program 68.63 16.418 100 11.2600 3.84713 100 69.26 15.696 100 70.61 15.128 100 .4700 .50161 100 .3400 .47610 100 Correlations Grade in writing in percent Number of hours studying per week Grade in math in percent Pearson Correlation Grade in writing in percent Number of hours studying per week Grade in math in percent Grade in reading in percent Participant sex at birth whether or not participants completed a study program Sig. (1-tailed) Grade in writing in percent Number of hours studying per week Grade in math in percent Grade in reading in percent Participant sex at birth whether or not participants completed a study program N Grade in writing in percent Number of hours studying per week Grade in math in percent Grade in reading in percent 1.000 .046 .813 .959 .046 1.000 .023 .034 .813 .023 1.000 .803 .959 .034 .803 1.000 .433 -.001 .105 .429 .232 -.043 .100 .167 . .326