T Tests
Methods
Data was analyzed from the SLLA scores of previous graduate students in the Leadership program. First, I deleted graduates who were missing some data in Excel. Next, data was copied into two columns labeled Cohort and Principal Corps (PC). The goal was to see if there was a significant difference between the SLLA scores from the two populations. Will the difference between the two conditions (principal corps and cohort graduate) in scores make a significant difference? The question Excel’s data analysis add-in tool created a t- test. I clicked on t-test with two samples, assuming equal variances. Variable one included the Principal Corps students because they had the highest mean or average of 177.70. The Cohort students’ data was included in variable two on the input table. The hypothesized mean difference equaled a zero. The alpha score equal 0.05. I enter the data and created a table. A third column was labeled to include the difference between the SLLA mean scores of the two sample populations. The null hypothesis is the populations are equal as respect to the dependent variables.
Findings
t-Test: Two-Sample Assuming Equal Variances PC 1 COHORT 2
Mean 177.7037037 173.7446809
Variance 70.21652422 42.02013269
Observations 27 94
Pooled Variance 48.18068882…show more content… The dependent variables are the SLLA scores. First, the principal corps average scores were higher than the cohorts. The degree of freedom equals 119 which is the total population minus one (n-1). The t-Stat equals 2.61 which conclude the standard deviation away from the mean. Now, I check the t Distribution table from Schools and Data, Creighton, (2007) on page 180 to see the calculation of the critical t-value of the (df) degree of freedom for 1.960. The calculated p value with two tails is 0.01. The p value is less than the alpha level of 0.05 so we can reject the
