OverviewRecall that samples are used to generate a statistic, which businesses use to estimate the population parameter. You have learned how to take samples from populations and use them to produce statistics. For two quantitative variables, businesses can use scatterplots and the correlation coefficient to explore a potential linear relationship. Furthermore, they can quantify the relationship in a regression equation.PromptThis assignment picks up where the Module Two assignment left off and will use components of that assignment as a foundation.You have submitted your initial analysis to the sales team at D.M. Pan Real Estate Company. You will continue your analysis of the provided Real Estate County Data spreadsheet using your selected region to complete your analysis. You may refer back to the initial report you developed in the Module Two Assignment Template to continue the work. This document and the National Statistics and Graphs spreadsheet will support your work on the assignment.Note: In the report you prepare for the sales team, the dependent, or response, variable (y) should be the median listing price and the independent, or predictor, variable (x) should be the median square feet.Using the Module Three Assignment Template, specifically address the following:Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.Determine r: Determine r and what it means. (What is the relationship between the variables?)Determine the strength of the correlation (weak, moderate, or strong).Discuss how you determine the direction of the association between the two variables.Is there a positive or negative association?What do you see as the direction of the correlation?Examine the Slope and Intercepts: Examine the slope b1{"version":"1.1","math":"b1"} and intercept b0{"version":"1.1","math":"b0"}.Draw conclusions from the slope and intercept in the context of this problem.Does the intercept make sense based on your observation of the line of best fit?Determine the value of the land only.Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept.Determine the R-squared Coefficient: Determine the R-squared value.Discuss what R-squared means in the context of this analysis.Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:Is the square footage for homes in your selected region different than for homes overall in the United States?For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?Use the regression equation to estimate how much you would list your house for if it was 1,200 square feet.What square footage range would the graph be best used for?Guidelines for SubmissionSubmit your completed Module Three Assignment Template as a Word document that includes your response and supCompetenciesIn this project, you will demonstrate your mastery of the following competencies:Apply statistical techniques to address research problemsPerform regression analysis to address an authentic problemOverviewThe purpose of this project is to have you complete all of the steps of a real-world linear regression research project starting with developing a research question, then completing a comprehensive statistical analysis, and ending with summarizing your research conclusions.ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict median housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the median housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate County Data spreadsheet (both found in the Supporting Materials section) for your statistical analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.Define the question your report is trying to answer.Explain when using linear regression is most appropriate.When using linear regression, what would you expect the scatterplot to look like?Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.Data CollectionSampling the data: Select a random sample of 50 counties.Identify your response and predictor variables.Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables.Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales?Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.Explain if a regression model is appropriate to develop based on your scatterplot.Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.Find r: Find the correlation coefficient (r).Explain how the r value you calculated supports what you noticed in your scatterplot.Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.Determine the strength of the linear regression equation you developed.Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results.Did you see the results you expected, or was anything different from your expectations or experiences?What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.What to SubmitTo complete this project, you must submit the following:Project One Template: Use this template to structure your report, and submit the finished version as a Word document.Supporting MaterialsThe following resources may help support your work on the project:Document: National Statistics and GraphsUse this data for input in your project report.Spreadsheet: Real Estate County DataUse this data for input in your project report.porting charts/graphs. The following resources support your work on this assignment:

Please answer the attached 41 statistics questions. No need to show work. Just select the correct answer choice. 1.When the regression line is written in standard form (using z scores), the slope is called zr.True or False? 2. The coefficient of determination is given by SSExplained/SST.True or false? 3. Nonparametric tests are useful for data that are measured only at the nominal or ordinal level of measurement.True or false? 4. The χ2 distribution is a positively skewed distribution.True or false ?5. The χ2 goodness of fit test and the χ2 test of independence are useful only if you have interval/ratio data.True or False? 6. Dependent samples, where each is measured on one dichotomous variable, can be analyzed using the McNemar test for significance of change.True or false? 7. Parametric tests are usually more powerful than their nonparametric analogs.Group of answer choicesTrue or False ? 8. A value of Y as predicted from the regression line is symbolized by .True or false? 9. A scatter diagram plots which of the following? Group of answer choicesthe distribution of the dependent variablethe distribution of the independent variableresiduals on one axis and the independent variable on the otherone variable on the X axis and another on the Y axis10. If it is impossible to determine whether the points in a scatter diagram tend from lower right to upper left or from upper right to lower left, the correlation is probablyGroup of answer choicesnegativepositivezero or close to zero11. Which of the following values for a correlation coefficient would indicate the strongest degree of relationship?Group of answer choices-.69+.59 c. +.03 d. -.3512. If ΣzXzY = 4 and n = 9, r isGroup of answer choicesa. +.50b. -.50c. 0d. impossible to determine from the information provided13. _ is the appropriate correlation coefficient for interval/ratio data; ____ is the appropriate correlation coefficient for ordinal data.Group of answer choicesSpearman's rS / Pearson's rSpearman's rS / no statisticPearson's r / Spearman's rSPearson's r / no statistic14. Exhibit 16-1Suppose you are interested in the relationship between number of piano lessons and skill as a piano player. You obtain reports about the number of lessons 50 children have had, and then have judges rate the skill of the piano players on a scale from 1 to 100 (100 being "excellent"). Then you compute a correlation coefficient for these data.Refer to Exhibit 16-1. You would expect that the correlation coefficient would probably beGroup of answer choicesonenegativepositivezero15. The appropriate standard score formula for Pearson's product-moment correlation coefficient for a sample isGroup of answer choicesρ = r = ρ = r = 16. A correlation coefficient ranges from ____ to ____.Group of answer choicesThe correlation coefficient can take any value and is not limited by any range.0 to 1 c. 0 to 100 d. -1 to 117. If you superimpose a tic-tac-toe diagram on a scatterplot, a point in the upper left corner of the tic-tac-toe diagram tends to make the correlation coefficient ____ because ____.Group of answer choicesnegative, zX and zY are both negativepositive, zX and zY are both negativenegative, zX is negative but zY is positivepositive, zX is negative but zY is positive18. The values of Y as predicted from the regression line are symbolized by?19. The error of prediction for the ith individual is given byGroup of answer choicesei = Yi = ei = ei = 20. The slope of a straight line is defined asGroup of answer choicesthe change in Y divided by the change in Xthe value of Y when X = 0the value of X when Y = 0the change in X divided by the change in Y21. The intercept of a straight line is defined asGroup of answer choicesthe value of Y when X = 0the change in Y divided by the change in Xthe change in X divided by the change in Ythe value of X when Y = 022. When the regression line is written in standard form (using z scores), the intercept isGroup of answer choiceszarzb023. Assume that = 29.6 and sY = 5.3. In which case is the standard error of estimate smallest?Group of answer choicesr = .7; sX = 4r = .9; sX = 12r = .4; = 100r = .1; = 1024. The coefficient of determination isGroup of answer choicesalways larger than sYanother name for the Pearson ralways smaller than sYequal to r225. The coefficient of determination is equal toGroup of answer choicesSSExplained/SSTrSSError/SST(SSExplained + SSError)/SST26. If a car has ten independent steering wheels with ten independent drivers, and each contributes equally to the direction that the car takes, the correlation between any one steering wheel and the direction the car takes is approximatelyGroup of answer choices0.1.9.327. Assume that IQ has mean 100 and standard deviation 15 for both boys and girls, and that the correlation between brother's and sister's IQ is .6. Suppose you know that John's IQ is 110. What should you predict his sister's IQ to be?Group of answer choices1151101009410628. What is ?Group of answer choicesThe equation for predicting variable X from variable YThe equation for the regression lineThe equation for the true scoreThe equation to decide why to wear a hat29. What two pieces of information are needed when drawing a regression line?Group of answer choicesThe value of X and the value of aThe standard error of the estimate and the correlation coefficientThe slope and the interceptRaw score and true score30. When are you most likely to see regression to the mean?Group of answer choicesWhen you select a sample based on extremely low scoresWhen the correlation coefficient is smallWhen you select a sample based on extremely high scoresAll of the above31. "nonparametric""parametric"DesignAt least nominalAt least ordinalNormalOne sample<Problem 1>--One samplet or z testTwo independentχ2 test of<Problem 2>Two independ.samplesindependencesample t testTwo dependent<Problem 3>Wilcoxon matchedTwo dependentsamplespairs signed-sample t testranks testk independentχ2 test of<Problem 4>One-waysamplesindependenceANOVARefer to Exhibit 18-1. The table shows comparisons between parametric and non parametric tests. Which test should replace the one marked <Problem 1>?Group of answer choicesMann-Whitney U-testGoodness of fit testKruskal-Wallis H-testStevens-Johnson S-testMcNemar test for significance of change32. If we had nominal data and our null hypothesis was that the shape of a distribution did not depend on the value of another variable we would use theGroup of answer choicesχ2 goodness of fit testWilcoxon matched-pairs signed-rank testχ2 test of independenceMann-Whitney U test33. Which of the following is true?Group of answer choicesThe χ2 statistic is a symmetric distribution.The χ2 statistic, like z, has no degrees of freedom.One must specify, as one does when using F, two sets of degrees of freedom when using the χ2 distribution.The χ2 statistic approaches a normal distribution when the degrees of freedom is large.34. Exhibit 18-2Suppose I build a card shuffler, and I wish to know whether it is effective. I take a standard bridge deck (52 cards in 4 suits: 13 Clubs, 13 Diamonds, 13 Hearts, and 13 Spades), use my shuffler on it, and draw a card, noting its suit. I repeat this process 100 times, and obtain the following sample distribution: 23 Clubs, 25 Diamonds, 26 Hearts, and 26 Spades.Refer to Exhibit 18-2. The proper test to use isGroup of answer choicesMann-Whitney U-testgoodness of fit testWilcoxon testKruskal-Wallis H-test35. Exhibit 18-2Suppose I build a card shuffler, and I wish to know whether it is effective. I take a standard bridge deck (52 cards in 4 suits: 13 Clubs, 13 Diamonds, 13 Hearts, and 13 Spades), use my shuffler on it, and draw a card, noting its suit. I repeat this process 100 times, and obtain the following sample distribution: 23 Clubs, 25 Diamonds, 26 Hearts, and 26 Spades.Refer to Exhibit 18-2. Which of the following is true?Group of answer choicesThe appropriate statistic is FThe number of degrees of freedom is 1My shuffler is biased because the sample distribution should have been 25, 25, 25, 25The number of degrees of freedom is 336. Exhibit 18-3Observed values of two variables:Variable IValue 1Value 2Row TotalValue 11020 30Variable IIValue 23040 70Column Total4060100Refer to Exhibit 18-3. If we had a 4 × 4 contingency table, degrees of freedom for the x2 test of independence would beGroup of answer choices1512916837. Exhibit 18-3Observed values of two variables:Variable IValue 1Value 2Row TotalValue 11020 30Variable IIValue 23040 70Column Total4060100Refer to Exhibit 18-3. In the contingency table above, what is the expected frequency of the upper left cell?Group of answer choices4010123038. Suppose we use a 9-point rating scale, and rate four subjects as shown in the table below. Then we convert those ratings to ranks so that the lowest rating is assigned a rank of 1.SubjectRatingGeorge4Sam2Oscar5Bill4Jack8Oscar's rank isGroup of answer choices3415239. When choosing between parametric and nonparametric tests, which of the following is true?Group of answer choicesYou may always perform a nonparametric test even if a parametric test is also appropriate.The larger the sample size, the less critical are violations of assumptions about normality.Analysis of variance has been shown to be robust to violations of the assumption of normality.All of the above are true.Parametric tests are usually more powerful than nonparametric tests.40. There are two kinds of nonparametric tests, those ____ and those ____.Group of answer choicesbased on inferences, based on statisticsbased on parameters, based on pluralismbased on order, not based on orderbased on statistics, based on inferences41. If we had nominal data and our null hypothesis was that the sampled data came from a specified distribution we would use theGroup of answer choicesχ2 test of independenceWilcoxon matched-pairs signed-rank testχ2 goodness of fit testMann-Whitney U test

22 question test, show work and help me understand please.