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Exercise 16 Understanding Independent samples t-Test
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Exercise 16 Understanding Independent samples t-Test
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Exercise 16: Understanding Independentsamples t-Test
Read the following exercises and submit your answers to "Questions to be graded" questions:
1. What do degrees of freedom (df) mean? Canbulat et al. (2015) did not provide the dfs in their study?
Why is it important to know the df for a t ratio? Using the df formula, calculate the df for this study.
The number of degrees of freedom generally refers to the number of independent observations in
a sample minus the number of population parameters that must be estimated from sample data.
(88 + 88) -2= 174. Degrees of freedom are important because it gives the number of values in a
study that have the freedom to vary. This number also helps verify the validity of the null
hypothesis
2. What the means and standard deviations (SDs) for age for the Buzzy intervention and control
groups? What statistical analysis is conducted to determine the difference in means for age for the
two groups? Was this an appropriate analysis technique? Provide a rationale for your answer Buzzy
mean 8.25 with SD 1.51 Control Mean 8.61 with SD 1.69. A t-test was conducted. Yes, it was an
appropriate analysis technique because it examines differences between the two groups at a ratio
level. The two groups would need to be similar for accuracy of the testing
3. What are the t value and p value for the age? What do these results mean? t -1.498 p-value is .
136. This means there is no significant differences between the two groups where age is
concerned because the p is greater than the level of significance set at x = 0.05
4. What are the assumptions for conducting the independent samples t test? The t-test for
independent samples or groups includes the following assumptions: Raw scores in the population
are normally distributed, dependent variables are measured at interval or ratio levels, the two
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