Scenario

You have been hired by your regional real estate company to determine if your region's housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report:

Are housing prices in your regional market higher than the national market average?

Is the square footage for homes in your region different than the average square footage for homes in the national market?

For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market?

You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, com plete the statistical analyses, and provide a report to the regional sales director. You will do so by co mpleting the Project Two Template located in the What to Submit area below.

Directions

Introduction

Purpose: What was the purpose of your analysis, and what is your approach?

Define a random sample and two hypotheses (means) to analyze.

Sample: Define your sample. Take a random sample of 100 observations for your region.

Describe what is included in your sample (i.e., states, region, years or months).

Questions and type of test: For your selected sample, define two hypothesis questions and the appropriate type of test hypothesis for each. Address the following for each hypothesis:

Describe the population parameter for the variable you are analyzing.

Describe your hypothesis.

Describe the inference test you will use.

Identify the test statistic.

Level of confidence: Discuss how you will use estimation and conference intervals to help you solve the problem.

1-Tailed Test

Hypothesis: Define your hypothesis.

Define the population parameter.

Write null (Ho) and alternative (Ha) hypotheses.

Specify your significance level.

Data analysis: Analyze the data and confirm assumptions have not been violated to co mplete this hypothesis test.

Summarize your sample data using appropriate graphical displays and summary statistics.

Provide at least one histogram of your sample data.

In a table, provide summary statistics including sample size, mean, median, and standard deviation.

Summarize your sample data, describing the center, spread, and shape in comparison to the national information.

Check the conditions.

Determine if the normal condition has been met.

Determine if there are any other conditions that you should check and whether they have been met.

Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.

Calculate the hypothesis statistics.

Determine the appropriate test statistic (t).

Calculate the probability (p value).

Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.

Relate the p value and significance level.

Make the correct decision (reject or fail to reject).

Provide a conclusion in the context of your hypothesis.

2-Tailed Test

Hypotheses: Define your hypothesis.

Define the population parameter.

Write null and alternative hypotheses.

State your significance level.

Data analysis: Analyze the data and confirm assumptions have not been violated to co mplete this hypothesis test.

Summarize your sample data using appropriate graphical displays and summary statistics.

Provide at least one histogram of your sample data.

In a table, provide summary statistics including sample size, mean, median, and standard deviation.

Summarize your sample data, describing the center, spread, and shape in comparison to the national information.

Check the assumptions.

Determine if the normal condition has been met.

Determine if there are any other conditions that should be checked on and whether they have been met.

Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs.

Calculate the hypothesis statistics.

Determine the appropriate test statistic (t).

Determine the probability (p value).

Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.

Relate the p value and significance level.

Make the correct decision (reject or fail to reject).

Provide a conclusion in the context of your hypothesis.

Comparison of the test results: See Question 3 from the Scenario section.

Calculate a 95% confidence interval. Show or describe your method of calculation.

Interpret a 95% confidence interval.

Final Conclusions

Summarize your findings: Refer back to the Introduction section above and summarize your findings of the sample you selected.

Discuss: Discuss whether you were surprised by the findings. Why or why not?

Which of the following statements are TRUE regarding Central Limit Theorem? CCS The central limit theorem gives the exact probability of estimating the true population mean. Chart / Roll The central limit theorem only applies when the population distribution is normal. The range of values for the sampling distribution of means is larger than the range of values in the population. The central limit theorem requires that all samples are randomly selected from a single population.Question 16 (1 point) If five hundred confidence intervals, each having a level of confidence of 90%, were computed for a population mean / , approximately how many of the intervals would be expected to contain / ? 475 450 555.56 0.0018 Question 17 (1 point) A population is bimodal. A sample of size 39 is taken from this population. The distribution of sample means is approximately normal. What "idea" allows us to know this? Axioms of Probability Law of Large Numbers Fundamental Theorem of Calculus Central Limit Theorem