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Running and Interpreting a t-Test Using Excel

apply your knowledge of experimental research to
determine if there is a statistically significant difference between mean (average)
outcomes for an experimental (Intervention group) group and a control group. You will
run “descriptive statistics” and a “t-test” using a sample data scenario and set described
below. The descriptive statistics will tell you means and standard deviations regarding
the outcomes measured; the t-test will tell you if there is a statistically significant
difference between the two means of the outcomes measured.
Instructions:
In a hypothetical study, a researcher randomly assigned participants who had trouble
dieting into one of two groups – an experimental (Intervention group) or a control group.
In the experimental group, participants completed an intervention where were asked to
think about how life would be better if they dieted and how life would be worse if they
did not. Participants in the control group did not receive any sort of intervention. At the
start of the study, all participants weighed 300 pounds. A month after the study began,
participants were weighed again, and the number of pounds lost was recorded. The
data collected is listed below. It was hypothesized that participants in the intervention
group would lose more weight, on average, than participants in the control group

Full Answer Section

t-test:
- Perform an independent samples t-test to compare the means of the two groups.
- This test will provide a p-value, which indicates the probability of observing such a difference by chance alone.

Interpretation:

A statistically significant difference (typically defined by a p-value less than 0.05) between the means of the intervention and control group would support the hypothesis that the intervention led to greater weight loss.
A high p-value (greater than 0.05) suggests there's no significant difference in weight loss between the groups, and the observed difference could be due to chance.

Example with Hypothetical Data:

Group	Weight Loss (lbs)	Mean (lbs)	Standard Deviation (lbs)
Intervention	10, 8, 15, 12, 7	10.4	3.2
Control	5, 3, 2, 4, 1	3	1.4

drive_spreadsheetExport to Sheets Hypothetical t-test:

If the t-test resulted in a p-value less than 0.05, we could conclude that the intervention group lost a statistically significant amount of weight compared to the control group.
This would provide initial evidence that the intervention program might be effective in promoting weight loss.

Important Note: This is a hypothetical example; the actual analysis would require the full data set with individual weight loss values for each participant. Additionally, other factors like diet and exercise levels might need to be considered for a more comprehensive analysis.

Sample Answer

This scenario describes a research experiment to determine if an intervention program can promote weight loss compared to a control group. We can analyze the data using descriptive statistics and a t-test to assess the hypothesis.

Data:

We don't have the actual weight loss data, but we know all participants started at 300 pounds and their weight loss was recorded after a month.

Analysis Steps:

Descriptive Statistics:
- Calculate the mean (average) weight loss for both the intervention and control groups.
- Calculate the standard deviation for weight loss in both groups. This shows how spread out the data points are within each group.