Complete parts​ (a) through​ (d) below. Determine the​ p-value in​ (a) and interpret its meaning. In addition to equal​ variances, what other assumption is necessary in​ (a)? Construct a 95​% confidence interval estimate of the difference between the population means of developed countries and emerging countries.

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The time required to start a​ business, defined as the number of days needed to complete the procedures to legally operate a​ business, in 20 developed countries and 20 emerging countries is included in the accompanying table. Complete parts​ (a) through​ (d) below.

Determine the​ p-value in​ (a) and interpret its meaning.

In addition to equal​ variances, what other assumption is necessary in​ (a)?

Construct a 95​% confidence interval estimate of the difference between the population means of developed countries and emerging countries.

The image provides information on the time required to start a business, measured in the number of days needed to complete the necessary procedures for legal operation. This data includes 20 developed countries and 20 emerging countries.

The task is to determine if there is a significant difference in the mean number of days required to start a business between these two groups. The hypotheses and statistical test involved are explained below.

**Hypotheses:**

- **A.** 
  - Null hypothesis (\(H_0\)): \(\mu_1 \neq \mu_2\) 
  - Alternative hypothesis (\(H_1\)): \(\mu_1 = \mu_2\)

- **B.**
  - \(H_0\): \(\mu_1 = \mu_2\) 
  - \(H_1\): \(\mu_1 \neq \mu_2\)

- **C.**
  - \(H_0\): \(\mu_1 \geq \mu_2\) 
  - \(H_1\): \(\mu_1 < \mu_2\)

We need to select the appropriate hypotheses based on whether we're testing for equality or some other relationship between the means.

A t-statistic is calculated to compare the mean times for the two groups. The user is asked to compute this t-statistic for the given data:

\[ t_{\text{STAT}} = \]

**Data Table:**

- This window shows the number of days required to start a business for both developed and emerging countries.

  **Developed Countries (days):**
  - Minimum: 5
  - Maximum: 123
  - Sample Data: 28, 123, 31, 6, 5, 5, 5, 14, 6, 10

  **Emerging Countries (days):**
  - Minimum: 1
  - Maximum: 30
  - Sample Data: 30, 15, 7, 12, 5, 5, 15, 4, 6, 8

The analysis assumes that the population variances for both developed and emerging countries are equal, and it uses a significance level (\(\alpha\)) of 0.05. Further steps would involve calculating the mean and standard deviation of each group's data, followed by the t-test to determine if there is a statistically significant
Transcribed Image Text:The image provides information on the time required to start a business, measured in the number of days needed to complete the necessary procedures for legal operation. This data includes 20 developed countries and 20 emerging countries. The task is to determine if there is a significant difference in the mean number of days required to start a business between these two groups. The hypotheses and statistical test involved are explained below. **Hypotheses:** - **A.** - Null hypothesis (\(H_0\)): \(\mu_1 \neq \mu_2\) - Alternative hypothesis (\(H_1\)): \(\mu_1 = \mu_2\) - **B.** - \(H_0\): \(\mu_1 = \mu_2\) - \(H_1\): \(\mu_1 \neq \mu_2\) - **C.** - \(H_0\): \(\mu_1 \geq \mu_2\) - \(H_1\): \(\mu_1 < \mu_2\) We need to select the appropriate hypotheses based on whether we're testing for equality or some other relationship between the means. A t-statistic is calculated to compare the mean times for the two groups. The user is asked to compute this t-statistic for the given data: \[ t_{\text{STAT}} = \] **Data Table:** - This window shows the number of days required to start a business for both developed and emerging countries. **Developed Countries (days):** - Minimum: 5 - Maximum: 123 - Sample Data: 28, 123, 31, 6, 5, 5, 5, 14, 6, 10 **Emerging Countries (days):** - Minimum: 1 - Maximum: 30 - Sample Data: 30, 15, 7, 12, 5, 5, 15, 4, 6, 8 The analysis assumes that the population variances for both developed and emerging countries are equal, and it uses a significance level (\(\alpha\)) of 0.05. Further steps would involve calculating the mean and standard deviation of each group's data, followed by the t-test to determine if there is a statistically significant
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