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    Linear Regression

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    Linear Relations

    Which relationships are linear? a) Quantity Profit 0 $0 1 $1,500 4 $6,000 9 $13,500 b) Quantity Metal Used 0 0 oz 1 8 oz 2 18 oz 3 26 oz c) Quantity Fixed Expenses 0 $3,000 1 $3,000 3 $3,000 5 $3,000

    Linear Regression Paper

    Attached is my paper using linear regression. I need to understand the part with the residuals scatterplot -- how do the standardized predicted values against the studentized residuals differ or are the same? How is that an indicator of homoscedasticity? Also, is my 95% CI correct? Are the numbers correct? Did I explain

    Regression Type of Advertising Costs and Income

    The following data is given: TYPE OF ADVERTISING MY COST MY INCOME Local Newspaper $120 $1,100 "Thrifty Dime" $25 $600 Church Bulletins $40 $500 Flyers $60 $800 "Cheese Cake Man" $80 $1,000 Usi

    Standard Error of Estimate and Predictions Regarding Sales

    A. Determine the standard error of estimate. B. Suppose a large sample is selected (instead of just 10). About 95 percent of the predictions regarding sales would occur between what two values? Exercise 14: Number of Sales Number of Sales Contacts, ($ thousands),

    3 Regression/Testing Questions

    Question One. A researcher is interested in determining the effect of after-school programs on adolescent delinquency. He asks a small sample of students how many activities they participate in and he asks how many delinquent acts they have committed since the school year has begun. His data are below. Calculate the linear r

    With the information provided above please answer the followin questions: 1. Do the data suggest that size is useful as a predictor if price for custom homes in the Equestrain Estates? Perform the required hypothesis at the 0.01 level of significance. 2. a. Find a 99% confidence interval for the slope of the population regression line that relates price to size for custom homes in the Equestraion Estates. b. Interpret your answer to part (a). 3. a. Determine a point estimate for the mean price of all 2800-sq-ft Equestrain Estates home. b. Find 99% confidence interval for the mean price of all 2800-sq-ft Equestrain Estate. c. Find the predicted price of a 2800-sq-ft Equestrain Estate home. d. Determine a 99% prediction interval for the price of a 2800-sq-ft Equestrain Estate home. 4. At the 0.5% significance level, do the data provide sufficiant evidence to conclude that, for custom homes in the Equestrain Estates, size and price are positively linearly correlated?

    Hanna Properties specializes in custom-home resales in the Equestrian Estates, an exclusive subdivision in Phoenix, Arizona. A random sample of nine custom homes currently listed for sale provided the following information on size and price. Here, x denotes size, in hundreds of square feet, rounded to the nearest hundred, and y

    T2-18

    (See attached file for full problem description) An economist is interested to see how consumption for an economy (in billions) is influenced by gross domestic product (billions) and aggregate price (consumer price index). The Microsoft Excel output of this regression is partially reproduced below. SUMMARY OUTPUT Regre

    Risk and Return: Use spreadsheet or a calculator

    You are given the following set of data: Year NYSE Stock X 1 -26.5% -14.0% 2 37.2% 23.0 % 3 23.8% 17.5% 4 -7.2% 2.0% 5 6.6% 8.1% 6 20.5% 19.4% 7 30.6% 18.2% A) Use spreadsheet or a calculator with a linear regression to determine Stock X's beta coefficient B) Determine the arithmetic average rate

    Forecasting: Regression

    Using Excel, solve the following: 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 recor

    Theory, analysis and interpretation of regression

    Theory of regression: How does regression relate to linear algebra? Regression terms and symbols: What is the difference between strong negative and strong positive? Practical examples of regression analysis: When would you use regression correlation at a place of employment, or in education, or in politics? Interpre

    Linear regression

    Sales date for two years are as follows. Data are aggregated with two months of sales in each period. (see chart in attached file) a. Plot the data b. Fit a simple linear regression model to the sales data. c. Using the results from parts a and b, prepare a forecast for the next year.

    Economics - forecasting

    Determine the values for S o and g for continuous compounding. (See attached file for full problem description)

    Linear Regression for Share Prices

    The following data about share prices for companies of different sizes is given: Size X Price Share Y 1 9 10.8 2 94.4 11.3 3 27.3 11.2 4 179.2 11.1 5 71.9 11.1 6 97.9 11.2 7 93.5 11 8 70 10.7 9 160.7 11.3 10 96.5 10.6 11 83 10.5 12 23.5 10.3 13 58.7 10.7 14 93.8 11 15 34.4 10.8 a. Calculate the regressio

    Linear Regression For National Highway Association

    The national highway association is studying the relationship between the number of bidders on a highway project and the winning (lowest) bid for the project. Of particular interest is whether the number of bidders increase or decrease the amount of the winning bid. See attachment for the data. a. Determine the regression equ

    Regression on R&D vs. Annual Profits

    The data below record, for a sample of 10 firms, the number of staff employed in Research and Development (X), and annual profits in millions of pounds (Y). X: [0,16,10,1,5,7,11,13,9,4] Y: [12,60,30,11,15,18,32,45,25,14] (a) Perform a linear regression of profits on R&D staff, and hence predict (giving confidence interval

    Linear Regression and Correlation

    Linear Regression and Correlation Mr. William Profit is studying companies going public for the first time. He is particularly interested in the relationship between the size of the offering and the price per share. A sample of 15 companies that recently went public revealed the following information. (see the attached c

    Solving Linear Regression Problems

    Refer to the Schools data, which includes information on the 94 school districts in northwestern Ohio. Let the independent variable be the percent of families on welfare in the school district and the number of students in the district be the dependent variable. 1. Determine the regression equation. Comment on the values yo

    Linear Regression

    The following sample observations were randomly selected. X:5 3 6 3 4 4 6 8 Y:13 15 7 12 13 11 9 5 Determine the coefficient of correlation and the coefficient of determination. Interpret the association between X and Y

    Linear Regression

    A. Determine the regression equation. b. Determine the estimated sales if 40 contacts are made. X Y 14 24 12 14 20 28 16 30 46 80 23 30 48 90 50 85 55 120 50 110 c. Determine the standard error of estimate. d. Suppose a large sample is selected (instead of just 10). About 95 percent of the predictions r

    Cinergy Coal Procurement Problem

    1. Determine how much coal to purchase from each of the mining companies and how it should be allocated to the generating units. What is the cost to purchase, deliver, and process the coal? 2. Compute the average cost of coal in cents per million BTUs for each generating unit (a measure of the cost of fuel for the generating un

    Linear Regression

    Linear Regression Help.. Using the attached excel spreadsheet (database) Develop a Linear Regression model using intrinsic job satisfaction and extrinsic job satisfaction. Intrinsic will be the dependent variable and extrinsic the independent. Comment on the analysis (Rsq, Rsq adj, etc.). Provide not only the output of the

    Linear Regression

    A study of average hourly earnings in manufacturing is made. The results are: Year Earnings 1976 5.22 1977 5.68 1978 6.17 1979 6.7 1980 7.27 1981 7.99 1982 8.49 1983 8.83 1984 9.23 a. Using the least squares coded method, determine the equation for the straight line going through the

    Calculating Simple Linear Regression

    In fitting a least squares line to n=15 data points, the following quantities were computed: SSxx=55, SSyy=198, SSxy=-88, x-bar=1.3, and y-bar=35. a.) Find the least squares line. b.) Describe the graph of the least squares line. c.) Calculate SSE d.) Calculate s^2.

    Linear programming - daily production totals of a certain product

    As a supervisor of a production department, you must decide the daily production totals of a certain product that has 2 models, the deluxe and the special. The profit on the deluxe model is $12 per unit and the profit on the special model is $10 per unit. Each model goes through two phases in the production process, and th

    Linear Regression Lines

    Answer each question in order. Write the number of the question and answer all parts thoroughly. Use complete sentences and show all required work. Project for Unit 1 Infant Mortality Data - Linear Regression Lines Show All Work The following table shows the mortality rates (in deaths per 1000 live births) for male

    Correlation Analysis and Business Decisions

    A. How is correlation analysis used in a business decision? b. How can correlation analysis be misused to explain cause and effect relationship? c. How is coefficient of determination used to make decisions? d. What is the standard error of estimate? Describe with an example. e. What are the coefficients of the linea

    General Statistics

    Question 1 Assume that a sample of n pairs of data results in the given value of r. For alpha equal .05, determine if there is a significant linear relationship between x and y. Let n = 22, r = -0.087. Question 2 Assume that a sample of n pairs of data results in the given value of r. For alpha equal .05, determine if