**StatCrunch U: Survey Results**This report presents the analysis of survey data concerning gender distribution using StatCrunch. Below are the detailed results from various statistical analyses.### One Sample Proportion Confidence Interval- **Outcomes in**: Gender- **Success**: Female- **p**: Proportion of successes- **Method**: Standard-Wald**95% Confidence Interval Results:**| Variable | Count | Total | Sample Prop. | Std. Err. | L. Limit | U. Limit ||----------|-------|-------|--------------|-------------|------------|------------|| Gender | 55 | 100 | 0.55 | 0.049749372 | 0.45249302 | 0.64750698 |This table provides the confidence interval for the proportion of females in the survey, showing a sample proportion of 55%. The lower limit is approximately 45.25%, and the upper limit is approximately 64.75%.### Frequency Table Results for Gender- **Count**: 100| Gender | Frequency | Relative Frequency ||--------|-----------|--------------------|| Female | 55 | 0.55 || Male | 45 | 0.45 |This frequency table displays the distribution of gender in the sample. Females make up 55% of the population, while males make up 45%.### One Sample Proportion Hypothesis Test- **Outcomes in**: Gender- **Success**: Female- **p**: Proportion of successes- **\( H_0 \)**: p = 0.5- **\( H_A \)**: p ≠ 0.5**Hypothesis Test Results:**| Variable | Count | Total | Sample Prop. | Std. Err. | Z-Stat | P-value ||----------|-------|-------|--------------|-----------|--------|---------|| Gender | 55 | 100 | 0.55 | 0.05 | 1 | 0.3173 |This section details the hypothesis test evaluating whether the proportion of females differs from 50%. The p-value of 0.3173 indicates no significant difference at typical significance levels.These analyses summarize the gender distribution in the sample and the results of statistical tests regarding gender proportions. **3. What are the proportions of females and males at StatCrunchU?**a) Show that the conditions are met for the use of a normal model for a confidence interval (count of successes and failures are greater than 10).b) Determine a range of plausible values for this proportion by using StatCrunch to find a 95% confidence interval. Paste the StatCrunch printout below. (StatCrunch steps: Stat, Proportion Stats, One Sample, With Data.)c) Interpret your interval referring to females at StatCrunchU.d) Explain what is meant by “95% confident.”**4) Does your confidence interval support your hypothesis test? Explain.**

Note: Hi there! Thank you for posting the question. As your question has more than 3 parts, we have solved only the first three subparts for you. If you need any specific subpart to be answered, please re-submit the question by specifying the subpart number or name. Given information: The results of one proportion test and the confidence interval for single proportion are given.(a). Conditions required to perform one sample proportion test: The required conditions to perform one sample proportion test are given below: The sample must be randomly selected from the population. The size of the population should be at least 10 times larger than the population. That is, N ≥ 10n. The expected values of success and failure must be at least 10. That is, np ≥ 10 and n(1-p) ≥ 10. Check for the conditions: Given that the a simple random sample of size 100 is selected. This infers that the sample is selected randomly from the population. The sample size is n = 100, the population size will be quite large. Hence, the population will be at least 10 times larger than the population. The expected values of success and failure are obtained as given below: np=100×0.55=55>10n1-p=100×1-0.55=100×0.45=45>10 Therefore, all conditions are met to perform a one sample proportion test.(b). Determine the 95% confidence interval: From the accompanying output, the 95% confidence interval for the proportion of females is 0.45249302 and 0.64750698. (c). Interpret the interval: There is 95% confidence that the proportion of females in the population is between 0.45249302 and 0.64750698.