An investigator wants to test the claim that there is no difference of a new weight loss medication at reducing BMI (kg/m²). Suppose the following table represents the results from a SRS of individuals enrolled in the study. Assume a normal approximation is acceptable. (a=.01) Patient BMI pre test BMI post test 30.5 26.5 B 32.8 28.3 35.6 28.2 34.7 27.9 30.1 28.5 A) What type of t-test is this? B) Write our your null and alternative hypotheses C) Calculate a tstat

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### Practice Problems:

An investigator wants to test the claim that there is no difference of a new weight loss medication at reducing BMI (kg/m²). Suppose the following table represents the results from a sample from a SRS of individuals enrolled in the study. Assume a normal approximation is acceptable. (α = 0.01)

| Patient | BMI pre test | BMI post test |
|---------|--------------|---------------|
| A       | 30.5         | 26.5          |
| B       | 32.8         | 28.3          |
| C       | 35.6         | 28.2          |
| D       | 34.7         | 27.9          |
| E       | 30.1         | 28.5          |

#### A) What type of t-test is this?

#### B) Write out your null and alternative hypotheses

#### C) Calculate a t-stat

#### D) t-crit = ± _

#### E) p-value = _

#### G) Reject or Failed to reject the null hypothesis

#### H) Construct a 99% confidence interval and provide an interpretation. Does your interval further support your decision in the hypothesis test above?

### Explanation of the Table:

The table lists the Body Mass Index (BMI) values for five patients both before and after a test period, during which they were administered a new weight loss medication. The two columns labeled "BMI pre test" and "BMI post test" represent the measurements taken before and after the administration of the medication, respectively.

### Steps to Address Problems:

1. **Type of t-test:** Given the nature of the data (paired observations before and after treatment), a paired sample t-test is appropriate.
2. **Null and Alternative Hypotheses:**
   - Null hypothesis (H₀): There is no difference in BMI before and after the treatment (µD = 0).
   - Alternative hypothesis (H₁): There is a difference in BMI before and after the treatment (µD ≠ 0).
3. **Calculate a t-stat:** Use the differences between pre-test and post-test BMIs to calculate the test statistic.
4. **Critical t-value (t-crit):** Determine the critical value based on the t-distribution and degrees of freedom (n-1) at a significance level of 0.01.
5. **p-value:** Determine the probability that the
Transcribed Image Text:### Practice Problems: An investigator wants to test the claim that there is no difference of a new weight loss medication at reducing BMI (kg/m²). Suppose the following table represents the results from a sample from a SRS of individuals enrolled in the study. Assume a normal approximation is acceptable. (α = 0.01) | Patient | BMI pre test | BMI post test | |---------|--------------|---------------| | A | 30.5 | 26.5 | | B | 32.8 | 28.3 | | C | 35.6 | 28.2 | | D | 34.7 | 27.9 | | E | 30.1 | 28.5 | #### A) What type of t-test is this? #### B) Write out your null and alternative hypotheses #### C) Calculate a t-stat #### D) t-crit = ± _ #### E) p-value = _ #### G) Reject or Failed to reject the null hypothesis #### H) Construct a 99% confidence interval and provide an interpretation. Does your interval further support your decision in the hypothesis test above? ### Explanation of the Table: The table lists the Body Mass Index (BMI) values for five patients both before and after a test period, during which they were administered a new weight loss medication. The two columns labeled "BMI pre test" and "BMI post test" represent the measurements taken before and after the administration of the medication, respectively. ### Steps to Address Problems: 1. **Type of t-test:** Given the nature of the data (paired observations before and after treatment), a paired sample t-test is appropriate. 2. **Null and Alternative Hypotheses:** - Null hypothesis (H₀): There is no difference in BMI before and after the treatment (µD = 0). - Alternative hypothesis (H₁): There is a difference in BMI before and after the treatment (µD ≠ 0). 3. **Calculate a t-stat:** Use the differences between pre-test and post-test BMIs to calculate the test statistic. 4. **Critical t-value (t-crit):** Determine the critical value based on the t-distribution and degrees of freedom (n-1) at a significance level of 0.01. 5. **p-value:** Determine the probability that the
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