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Regression Analysis

Statistics: Normality, regression and hypotheses testing problems

Please use use the templates attached. 1. (a) Suppose you want to estimate the mean percentage of gain in per share value for growth-type mutual funds over a specific 2-year period. Ten mutual funds are randomly selected from the population of all the commonly listed funds. The percentage gain figures are shown below (negativ

Statistics: Auto parts distributor will estimate annual sales in April

See the attached file. Suppose that the sales manager of a large automotive parts distributor wants to estimate as early as April the total annual sales of a region. On the basis of regional sales, the total sales for the company can also be estimated. If, based on past experience, it is found that the April estimates of annu

Carpet City: Develop a linear regression model

Carpet City wants to develops a means to forecast it carpet sale. The store manager believes that the store's sale are directly related to the number of new housing starts in town. The manager has gathered data from county records on monthly house construction permits and from store records on monthly sales. Monthly Carpet Sa

A. Develop a linear regression for these data and forecast carpet sales if 30 construction permits for a new homes are filed. B. Determine the strength of the casual relationship between monthly sales and new home construction by using correlation.

24. Carpet city wants to develop a means to forecast its carpet sales. The store manager believes that the store's sales are directly related to the number of new housing starts in town. The manager has gathered data from county records on monthly house construction permits and from store records on monthly sales. These data are

Statistics: develop and assess a forecasting model for ice cream production

The Bee line Café is well known for its popular homemade ice cream, which it makes in a small plant in back of the café. People drive long distance to buy the ice cream. The two ladies who own the café want to develop a forecasting model so they can plan their ice cream production and determine the number of employees they n

Statistics Discussion: Common trend models; centered to moving average method

DQ3: (a) Name two advantages and two disadvantages of each of the common trend models (linear, exponential, quadratic). Explain! (b) When would the exponential trend model be preferred to a linear trend model? Explain! DQ4: One of the methods that is used to moderate (smooth) the peaks and valleys within a ti

Regression analysis in SPSS

Use the data set supplied (hypertension, diabetes, cholesterol in subjects, including medication, weight, age, etc) in doc sharing and using SPSS, provide the following for the variable(s) of your choice: 1. Frequency distribution of a variable and bar graph of the same variable 2. Descriptive of a continuous : mean, median,

Statistics

Please notice that we need to calculate the parameters in the linear equations through statistics and not through the mathematics [in Q1 & Q3]. Y= ax + b: here a and b must be calculated through statistical formaula and the steps must be shown. It is not accepted to just plot the data in Excel and fit a stright line to them t

Multiple Regression Analysis

Problem: The demand for airplane passengers (Y) is a function of a average fare (X1), the fare of the competing airline, and the annual per capital income of the passengers(X3) Passenger seat sold Fare of the Fare of the competing Annual Per Capital of the airline airline a

Rate of Return

1. If the daily stock price, x, of United Technology is normally distributed with mean 6.56 and standard deviation 2.4, calculate the probability that in a randomly selected ay the price will be between $3.25 and $7.36. Hint: Review normal distribution. 2. An industry is comparing its performance against an industry benchmar

Linear Regression and Correlation: Confidence Interval for Mean

1. The following sample observations were randomly selected. X: 4, 5, 3, 6, 10 Y: 4, 6, 5, 7, 7 a. Determine the regression equation. b. Determine the value of Y' when X is 7. c. Determine the standard error of estimate. d. Suppose a large sample is selected (instead of just 5). About 68% of the prediction

Seafood restaurant

The manager of a seafood restaurant was asked to establish a pricing policy on lobster dinners. Experimenting with prices produced the following data: Average Number Sold per Day, y Price, x 200 $6.00 190

Correlation and regression: key informaiton

Use the data in the table, which shows the personal income and outlays (both in trillions of dollars) for Americans for 11 recent years. (Source: U.S. Commerce Department, Bureau of Economic Analysis) Personal income, x Personal outlays, y 5.6 4.6 5.8 4.9 6.2 5.2 6.5 5.5 6.9 5.8 7.4 6.1 7.8

Regression model

The following data gives the starting salary for students who recently graduated from a local university and accepted jobs soon after graduation. The starting salary, grade jobs soon after graduation. The starting salary, grade- point average (GPA), and major (business or other) are provided. Salary $29,500 $46,000 $39,800 $36,

Calculate the regression equation

Calculate the regression equation using Excel, including the R Square, Slope, Intercept and the formula Y = a +bX with % Welfare as the X variable and % Passing as the Y variable.

Regression Analysis: Implementation and Interpretation

I. Simple Regression to Estimate Parameters. (A) Simple regression model with sales revenue as the dependent Y-variable and R&D expenditures independent X-variable. (B) Simple regression model with profits as the dependent Y-variable and R&D expenditures independent X-variable.

Simple Regression Analyses

Prepare a report using Excel as your processing tool to process three simple regression analyses. 1. First run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the data set as the dependent variable.

Correlation and regression analysis

Residual Plot: Consider the data in the table below. A. Examine the data and identify the relationship between x & y. B. Find the linear correlation coefficient & use it to determine whether there appears to be a significant linear correlation between x & y. C. Construct a scatter plot. What does it suggest about the relatio

Regression equation for predictions

Find the equation of the regression line for the given data. Use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown below. Calories, X 160 170 130 130 90 180 Sodium, Y 415

Regression analysis

Imagine you are a real estate investor presented with a regression analysis of home sales near one of your investment properties. Use Stat tools regression mod3l to determine: Which is a better predictor of selling price:appraised value, square footage, or number of bedrooms? A) How much value is added per $1000 OF APPR

Regression Analysis Significance in Statistics

Problem: Do Hispanics earn more than white individuals at a large company, for which lawsuit filed. Attached data include, 1. Employee ID, 2. Job title, 3. Ethnicity, 4. Yrs. Working. 1. Is pay different by ethnicity and if so are they statistically significant, and what is meaning of such. Consider some of the arguments t

Unit 5 Statistics Help...please

Hi, I need help with this assignment. I am using a different Dataset then what is in the solution library. My data set is 0903A.Xls.My school uses Turn it which is a similarity score and if it matches too high The assignment mentions a DATA SET 903A which i have provided - I have attached this information. Thank you and ple

Regression analysis problems - Bus Inc. sells widgets

Bus Inc. sells widgets. Sales dept says there is a positive linear relationship between the advertising expenditures and sales. Sales department recently analyzed the sales over 42 weeks. For each week in the sample, Bus Inc sales (SALES) and their advertising expenditures (ADVERT) were recorded. A simple regression analysis was

Statistic help

An agent for a residential real estate company in a large city would like to be able to predict the monthly rental cost of apartments based on the size of the apartment.At the .05 level of significance determine if the correlation between rental cost and apartment size is significant? Rent Size 950 850 1600 1450 1200 1085 1