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.
Note: There are 5 parts to this assignment each one on a separate page. Make sure to answer all parts.
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:
Descriptives |
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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 |
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freshman yr science score | |||
Levene Statistic | df1 | df2 | Sig. |
.565 | 3 | 196 | .639 |
ANOVA |
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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 |
Multiple Comparisons |
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Dependent Variable:Â Â 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. |
You can do this in bullet format, but make sure to use whole sentences.
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). |
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:
Model Summary |
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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 |
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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 |
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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 |
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:
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:
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