Statistics question This image is a snippet from a statistics problem interface, likely related to hypothesis testing involving proportions. **Elements in the Image:**1. **Input Fields:** - **p₀ (p sub zero):** A field for entering the null hypothesis proportion. - **x:** A field for entering the number of successes in the sample. - **n:** A field for entering the sample size. 2. **Dropdown Menu:** - Contains options for choosing the type of test to perform: - "< p₀" (less than p₀) - "≠ p₀" (not equal to p₀) - "> p₀" (greater than p₀)3. **Prop (Proportion) Dropdown:** - Likely to select a specific proportion for the test. 4. **Notation:** - "(Do not round.)" indicates that exact values should be used, not approximations.This form is used to configure and conduct statistical tests on sample data to determine whether the sample proportion differs from a hypothesized population proportion. **Hypothesis Testing for Sleepwalking Study**According to a reputable magazine, 33% of people in a certain large country have sleepwalked at least once in their lives. Suppose a random sample of 250 people showed that 60 reported sleepwalking. We will carry out the first two steps of a hypothesis test to determine if the proportion differs from 0.33, using a significance level of 0.05.**Step 1: Determine the Null and Alternative Hypotheses**- Null Hypothesis (H₀): \( p = 0.33 \)- Alternative Hypothesis (Hₐ): \( p \neq 0.33 \)(Enter integers or decimals. Do not round.)**Step 2: Check Conditions for the One-Proportion Z-Test**Select all the conditions that are not satisfied:- [ ] A. The Random Sample condition is not satisfied or cannot be reasonably assumed.- [ ] B. The Large Sample Size condition is not satisfied or cannot be reasonably assumed.- [ ] C. The Independence condition is not satisfied or cannot be reasonably assumed.- [x] D. The Large Population condition is not satisfied or cannot be reasonably assumed.- [ ] E. All conditions are satisfied or can be reasonably assumed.**Step 3: Identify Entries for Technology Input Figure**Fill in the values:- \( p_0 \): \( 0.33 \)- \( x \): \( 60 \)- \( n \): \( 250 \)- \( \text{prop} \): Not to be rounded.These values are essential inputs for statistical software or calculators used to perform the hypothesis test. The entries correspond to:- \( p_0 \): Hypothesized proportion- \( x \): Number of successes (people who reported sleepwalking)- \( n \): Total number of observations in the sample- prop: Sample proportion of successes (calculated as \( \frac{x}{n} \))This educational content serves to guide through the initial steps of hypothesis testing focused on understanding population proportions and assessing statistical significance.

Name: Statistics question This image is a snippet from a statistics problem
Uploaded: 2024-03-20T07:06:27.000Z
Channel: Bartleby
Description: Statistics question This image is a snippet from a statistics problem interface, likely related to hypothesis testing involving proportions. **Elements in the Image:**1. **Input Fields:** - **p₀ (p sub zero):** A field for entering the null hypothe

State the null and alternative hypotheses. Null Hypothesis: The population proportion who have sleepwalked is equal to 0.33. Alternate Hypothesis: The population proportion who have sleepwalked is not equal to 0.33. In statistical terms,All conditions are satisfied or reasonably assumed. Z test could be conducted to test the hypothesis. p0: It is the hypothesized proportion which we want to compare. x = Number of successes that is the number of people who step walked in the sample. n = sample size taken from the population prop: The ration of x and n