Question

I want you to conduct a hypothesis test for a difference of means for cholesterol levels between male and female students. There are 148 females and 164 males in our sample. You can treat this as a large sample problem and use z-values for confidence intervals and hypothesis tests (however, Excel uses a t-value in anything it calculates). The output from Microsoft Excel is given below to help. Your job wl be to find the right numbers in the output to help solve the problem EXCEL DESCRIPTIVE STATISTICS FOR CHOLESTEROL LEVELS OF MALES AND FEMALES Females Males Cholesterol Mean 200.318 196.085 Standard Error 0.881 0.966 Median 201 196 Mode 194 196 Standard Deviation 10.721 12.372 Sample Variance 114.939 153.072 0.493 Kurtosis 0.015 0.109 Skewnes:s 0.086 Range 47 61 Minimum 176 166 Maximum 223 227 32158 29647 Sum Count 164 148 Confidence Level (95.0%) 1.742 1.908 Next we want to do a confidence interval for difference of the two means. The Descriptive Statistics are given above. Put a 95% Confidence Interval around the difference of the female mean male mean. This will make clear the approach and meaning of a confidence interval of the difference of two means compared with the confidence interval for each mean. We can treat this as a large sample and use a z-value (If you use a t-value your answer will be the same within the specified rounding error) We will not assume equal variances. We want a 95% Confidence interval for the difference of the two means, what is the BOE for this Confidence Interval. Use 3 significant decimal places and use the proper rules of rounding.

Answer 1

To find the 95% confidence interval for the difference of means between male and female cholesterol levels, calculate the standard error and margin of error using the sample standard deviations and sample sizes.

Step-by-step explanation:

To find the 95% confidence interval for the difference of means between male and female cholesterol levels, you will need to calculate the standard error and the margin of error.

The standard error can be calculated using the formula:

SE = sqrt((SD1^2/n1) + (SD2^2/n2))

Where SD1 and SD2 are the standard deviations of the two samples, and n1 and n2 are the sample sizes. The margin of error is then calculated using the formula:

ME = Z * SE

Where Z is the z-value corresponding to the desired confidence level (for 95% confidence, Z is approximately 1.96).

The confidence interval is then given by: CI = (Mean 1 - Mean 2) +/- ME

Plugging in the values from the provided data:

SE = sqrt((10.721^2/148) + (12.372^2/164))

ME = 1.96 * SE

CI = (200.318 - 196.085) +/- ME