Assignment 10 Alternative | PSY 07301 Statistics in Psychology | Homework Solution - Grade One Essays

Assignment 10 Alternative | PSY 07301 Statistics in Psychology | Homework Solution

PSY 07301 Statistics in Psychology

Instructions: For each question, answer all items. Make sure that you are detailed when you answer the questions. As a rule of thumb, when you are answering any questions using statistics, you should include all statistics in the answer (e.g. if it asks about the mean, put the actual value of the mean in the sentence). Type your answers out underneath each question either bolded or in a different font color (or both). Please do not delete the questions or the output. When you are finished with the assignment, upload it as a .doc, .docx, or .pdf to the assignment on Canvas.

The analyses come from the high school exam data set. This data set includes information about how students in NY State performed on a bunch of standardized tests. In addition to the test scores, there is demographic information (ethnicity/race, gender) and school information (type of school, type of program). The analyses below use a variety of tests that look at the relationships between variables.

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Note: There are 5 parts to this assignment each one on a separate page. Make sure to answer all parts.

Part I: One-Way ANOVA

This analysis is looking at the relationship between ethnicity/race and freshman year science scores. Use the tables and graph included below to answer the following questions:

  1. What are the null and alternative hypotheses for this analysis?
  2. In a few sentences, describe the descriptive data for each ethnicity/race group (include N, mean, standard deviation, minimum, & maximum).
  3. Did we violate the assumption of homogeneity in this analysis? Include evidence for your answer (i.e. how do you know?).
  4. Were there significant differences in science scores between the different ethnicities?
  5. Based on the results of your analysis, should you analyze the post hoc tests?
    1. If yes, which groups are significantly different from each other? (List all).
    2. Explain what the post hoc tests tell us about the relationship between ethnicity and science scores.
  6. Complete Step 4 of hypothesis testing. Include your decision about the null hypothesis, a sentence describing the results (including post hoc tests), and the APA-style string of statistics.
  7. In your own words, what is the relationship between ethnicity and science scores?

PSY 07301 Statistics in Psychology

Descriptives

freshman yr science score
  N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum
Lower Bound Upper Bound
hispanic 24 45.3750 8.21881 1.67766 41.9045 48.8455 26.00 63.00
asian 11 51.4545 9.49067 2.86154 45.0786 57.8305 34.00 66.00
african-amer 20 42.8000 9.44569 2.11212 38.3793 47.2207 29.00 61.00
white 145 54.2000 9.09487 .75529 52.7071 55.6929 33.00 74.00
Total 200 51.8500 9.90089 .70010 50.4694 53.2306 26.00 74.00

Test of Homogeneity of Variances

freshman yr science score
Levene Statistic df1 df2 Sig.
.565 3 196 .639

 

ANOVA

freshman yr science score
  Sum of Squares df Mean Square F Sig.
Between Groups 3446.748 3 1148.916 14.021 .000
Within Groups 16060.752 196 81.943    
Total 19507.500 199      
Post Hoc Tests
Multiple Comparisons
Dependent Variable:   freshman yr science score
LSD
(I) Ethinicy/Race (J) Ethinicy/Race Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
Lower Bound Upper Bound
hispanic asian -6.07955 3.29600 .067 -12.5797 .4206
african-amer 2.57500 2.74069 .349 -2.8300 7.9800
white -8.82500* 1.99484 .000 -12.7591 -4.8909
asian hispanic 6.07955 3.29600 .067 -.4206 12.5797
african-amer 8.65455* 3.39801 .012 1.9532 15.3559
white -2.74545 2.83098 .333 -8.3285 2.8376
african-amer hispanic -2.57500 2.74069 .349 -7.9800 2.8300
asian -8.65455* 3.39801 .012 -15.3559 -1.9532
white -11.40000* 2.15922 .000 -15.6583 -7.1417
white hispanic 8.82500* 1.99484 .000 4.8909 12.7591
asian 2.74545 2.83098 .333 -2.8376 8.3285
african-amer 11.40000* 2.15922 .000 7.1417 15.6583
*. The mean difference is significant at the 0.05 level.

Part II: Correlation

  • Using the output below (investigating the relationship between different exam scores), describe all 3 different pairs of relationships (reading-writing; reading-math; math-writing). For each, make sure to include the following information:
  • Whether the relationship was significant.
  • If it was significant, whether it was a positive/negative relationship.
  • Describe the relationships (As X increases/decreases, Y increases/decreases).
  • APA string of statistics [r=r value, p=______]

You can do this in bullet format, but make sure to use whole sentences.

Correlations
Correlations
  reading score writing score math score
reading score Pearson Correlation 1 .597** .658**
Sig. (2-tailed)   .000 .000
N 200 200 200
writing score Pearson Correlation .597** 1 .056
Sig. (2-tailed) .000   .190
N 200 200 200
math score Pearson Correlation .658** .056 1
Sig. (2-tailed) .000 .190  
N 200 200 200
**. Correlation is significant at the 0.01 level (2-tailed).

 

  • Looking at the scatterplot below, describe the relationship between math scores (X) and social studies scores (Y). Make sure to describe the strength and direction of the relationship. You do not need to include an APA string of statistics for this question.

Part III: Regression

The output below is the result of investigating the predictive relationship between freshman year science scores and senior year science scores. Researchers wanted to see if they can predict senior year science scores from each student’s freshman year scores. Answer the following questions using the output below:

  • What is the correlation coefficient (r) for the relationship between senior and freshman year scores?
  • Does freshman year science scores significantly predict senior year science scores?
    • Write out the F statistical string associated with this relationship. [F(dfreg, dfres)=F value, p=________]
  • Write out the line of best fit equation for this relationship (Y=bX+a, substituting the b & a with values from the table).
    • If someone scored a 70 on their freshman year science test, based on the line of best fit, what would their predicted senior year score be?

PSY 07301 Statistics in Psychology

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .878a .771 .770 5.80149
a. Predictors: (Constant), freshman yr science score

 

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 22478.445 1 22478.445 667.862 .000b
Residual 6664.150 198 33.657    
Total 29142.595 199      
a. Dependent Variable: senior yr science score
b. Predictors: (Constant), freshman yr science score

 

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -2.613 2.192   -1.192 .235
freshman yr science score 1.073 .042 .878 25.843 .000
a. Dependent Variable: senior yr science score

Part IV: Chi Square Goodness of Fit Test

For this study, participants were split into 3 groups based on the type of exercise they engage in (martial arts, general exercise, or no exercise). I wanted to see if there were more people who do one type of exercise compared to the others. To do so, I ran a chi square goodness of fit test to determine whether there was a different number of participants in the groups. Answer the following questions using the output below:

  • How many people did I sample total?
  • Which of the exercise groups had more than the expected N?
  • Which of the exercise groups had less than the expected N?
  • Was there a significant difference in the number of participants in each group? How do you know?
  • Write out the statistical string of information for this test. It should be formatted like this: C2(df, N=##)= Chi-square value, p=###
    1. Make sure that you put the actual number in for the df, the chi-square value, and the ## after N and p
  • In your own words, what do the results of this test tell you about the distribution of participants in these exercise groups?

Part V: Chi Square Test of Independence

For this study, participants were split into 3 groups based on the type of exercise they engage in (martial arts, general exercise, or no exercise). I wanted to see if there was a difference in the proportion of male and female participants in the different exercise types. To do so, I ran a chi square test of independence to determine whether there was a significant relationship between the variables. Answer the following questions using the output below:

  • How many people did I sample total?
  • Which of the exercise groups had the same amount of male and female participants?
  • Which gender had higher numbers in general exercise?
  • Which gender had higher numbers in the no exercise group?
  • Which exercise group had the highest number of people total in it?
  • Was there a significant relationship between exercise type and gender? How do you know?
  • Write out the statistical string of information for this test. It should be formatted like this: C2(df, N=##)= Chi-square value, p=### Get Skunk Works Assignment Help!!
    1. Make sure that you put the actual number in for the df, the chi-square value, and the ## after N and p
  • In your own words, what do the results of this test tell you about these 2 variables?

 

Assignment 10 Alternative | PSY 07301 Statistics in Psychology

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