Results : Correlation Pearson's Partial Correlations Variable JWB average IRMA total 2 1. JWB average Pearson's r — p-value — 2. IRMA total 2 Pearson's r 0.597 — p-value < .001 — Note. Conditioned on variables: Gen ID. Linear Regression Model Summary - IRMA total Model R R² Adjusted R² RMSE M₀ 0.000 0.000 0.000 5.450 M₁ 0.779 0.607 0.560 3.614 Note. M₁ includes Hostle Average, Gen ID, JWB average ANOVA Model Sum of Squares df Mean Square F p M₁ Regression 505.296 3 168.432 12.897 < .001 Residual 326.497 25 13.060 Total 831.793 28 Note. M₁ includes Hostle Average, Gen ID, JWB average Note. The intercept model is omitted, as no meaningful information can be shown. Coefficients Model Unstandardized Standard Error Standardized t p M₀ (Intercept) 17.276 1.012 17.069 < .001 M₁ (Intercept) -6.866 5.360 -1.281 0.212 Hostle Average 5.836 1.708 0.485 3.416 0.002 Gen ID -3.251 2.281 -0.185 -1.425 0.166 JWB average 0.428 0.145 0.417 2.941 0.007 How can we answer the questions below based on the results above? Research question • A few sentences on what you wished to accomplish in this study. An overview. • State the hypotheses, present the results and your conclusions. • Make a general conclusion about your overview. Finally, I don't know where to put this, so I'll put this here: the degrees of freedom for a partial correlation significant test is df=n-2-c. C is the number of control variables (variables being held constant). In this example, C=1. Example: This lab reanalyzed our data collected on just world beliefs, ambivalent sexist and rape myth acceptance. We hypothesized that once controlling for gender, self just world beliefs, and hostile sexist beliefs will - separately - have a positive relationship with rape myth acceptance. This led to several specific hypotheses: Hypothesis 1a: Men will be more likely to adhere to rape myths than women. The correlation of the participants' self-identified gender (GenID) was negative and non-significant [r (21)=-0.31, p>.05]. Since females were coded with a zero, a negative correlation means that females had a higher endorsement of items on the Illinois Rape Myth Acceptance scale (IRMA). Hypothesis la was not supported. Hypothesis 2a: JWB-self will be positively associated with rape myth acceptance after partialing out the effects of gender. The correlation of the participants' level of JWB-S and Spring, 2025 Psy 430 Dr Ashton Experimental Methods IRMA was significant and in the correct direction [pr(21)=.74, p<.001]. Thus, Hypothesis 2a was supported. Hypothesis 3: JWB-S, HS and GenID will predict RMA. An MRC was conducted predicting RMA scores using GenID, HS and JWB-S scores. These variables significantly predicted RMA scores [R'=0.90, F(3,23) = 27.02, p<.001].

Ciccarelli: Psychology_5 (5th Edition)
5th Edition
ISBN:9780134477961
Author:Saundra K. Ciccarelli, J. Noland White
Publisher:Saundra K. Ciccarelli, J. Noland White
Chapter1: The Science Of Psychology
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Results : Correlation Pearson's Partial Correlations Variable JWB average IRMA total 2 1. JWB average Pearson's r — p-value — 2. IRMA total 2 Pearson's r 0.597 — p-value < .001 — Note. Conditioned on variables: Gen ID. Linear Regression Model Summary - IRMA total Model R R² Adjusted R² RMSE M₀ 0.000 0.000 0.000 5.450 M₁ 0.779 0.607 0.560 3.614 Note. M₁ includes Hostle Average, Gen ID, JWB average ANOVA Model Sum of Squares df Mean Square F p M₁ Regression 505.296 3 168.432 12.897 < .001 Residual 326.497 25 13.060 Total 831.793 28 Note. M₁ includes Hostle Average, Gen ID, JWB average Note. The intercept model is omitted, as no meaningful information can be shown. Coefficients Model Unstandardized Standard Error Standardized t p M₀ (Intercept) 17.276 1.012 17.069 < .001 M₁ (Intercept) -6.866 5.360 -1.281 0.212 Hostle Average 5.836 1.708 0.485 3.416 0.002 Gen ID -3.251 2.281 -0.185 -1.425 0.166 JWB average 0.428 0.145 0.417 2.941 0.007 How can we answer the questions below based on the results above? Research question • A few sentences on what you wished to accomplish in this study. An overview. • State the hypotheses, present the results and your conclusions. • Make a general conclusion about your overview. Finally, I don't know where to put this, so I'll put this here: the degrees of freedom for a partial correlation significant test is df=n-2-c. C is the number of control variables (variables being held constant). In this example, C=1. Example: This lab reanalyzed our data collected on just world beliefs, ambivalent sexist and rape myth acceptance. We hypothesized that once controlling for gender, self just world beliefs, and hostile sexist beliefs will - separately - have a positive relationship with rape myth acceptance. This led to several specific hypotheses: Hypothesis 1a: Men will be more likely to adhere to rape myths than women. The correlation of the participants' self-identified gender (GenID) was negative and non-significant [r (21)=-0.31, p>.05]. Since females were coded with a zero, a negative correlation means that females had a higher endorsement of items on the Illinois Rape Myth Acceptance scale (IRMA). Hypothesis la was not supported. Hypothesis 2a: JWB-self will be positively associated with rape myth acceptance after partialing out the effects of gender. The correlation of the participants' level of JWB-S and Spring, 2025 Psy 430 Dr Ashton Experimental Methods IRMA was significant and in the correct direction [pr(21)=.74, p<.001]. Thus, Hypothesis 2a was supported. Hypothesis 3: JWB-S, HS and GenID will predict RMA. An MRC was conducted predicting RMA scores using GenID, HS and JWB-S scores. These variables significantly predicted RMA scores [R'=0.90, F(3,23) = 27.02, p<.001].
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