The following data refers to gross earned income, in thousands of dollars per year, and level of taxation on that income. Determine whether a relation exists between these two factors, and if so its strength, then predict how much tax any other individual would have to pay in this mythical society. INCOME 7
Forecasting: The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. Use time series decomposition to forecast quarterly sales for the next year.
The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. Use time series decomposition to forecast quarterly sales for the next year. Quarter Sales Quarter Sales 1 160 5 215
Do literacy and GDP explain life expectancy? Would you include any other independent variables? Explain the attached regression table and ANOVA table as a whole in detail as it correlates to the variables.
I need help with estimate simple linear regression model for the management of Beta Technologies, Inc. is trying to determine the variable that best explains the variation of employee salaries using a simple of 52 full time employees in the attached file. I need to identify which of the following has the strongest linear relatio
I need to show a scatter diagram using the molecular weight as my x-axis. Consider the following data on 20 chemical reactions, with Y = chromatographic retention time (seconds) and X = molecular weight (gm/mole). (a) Make a scatter plot. (b) Use Excel to fit the regression, with fitted equation and R2. (c) In your own words,
Please see the attached file. I have 2 data sets that determine a y-value based on known x-values (the x-values are given as temp degrees C) ---- each of those actual line graphs have been fitted with an approximate "best fit" line determined by Excel with 2 separate 6th order line equations. Our homework asks us to add th
Pilot Farm Project Probability Weather Peas Corn Tobacco Beets 0.3 Dry 20 15 30 40 0.5 Moderate 35 20 25 40 0.2 Damp 40 30 25 40 Net Income $1.00 $1.50 $1.00 $0.50 per bushel a. Create a treeplan for the project b. What is the expected outcome? c. If the weather is expected to be 10% d
Ho: Total home cost increases with additional square feet Ha: Total home cost does not increase with additional square feet Define bivariate regression, discuss fitted regression and using regression for prediction purposes. Please see attached data and help me to understand what each section means.
Is this regression significant? How do you know? Please see the attached file.
Please see the attached file for complete questions. 1. The following results were obtained as part of a simple linear regression analysis. We wish to test Ho: β = 0. The computed value of the test statistics is ________ 2. The following results were obtained as part of a simple linear regression analysis. For
THE NASDAQ stock market includes small-and medium-sized companies, many of which are in high-tech industries.
THE NASDAQ stock market includes small-and medium-sized companies, many of which are in high-tech industries. Because of the nature of these companies, the NASDAQ tends to be more volatile than the Dow Jones Industrial Average or the S&P 500. The weekly values for the NASDAQ during the first 20 weeks of 2006 are listed in the d
The mean time to locate flight information on internet websites of the major airline companies is generally 2 to 3 minutes
I need all of the formulas explained as well as all of the answers. Please see the attached file.
Please see the attached file. 8. Consumer Debt Credit card debt has risen steadily over the years. The table above gives the average U.S. credit card debt (in dollars) per household. Years are represented as the number of years since 1900. (The table above includes all credit cards and U.S. households with at least one credi
Below is a section of output which used data collected on different brands of cigarettes. Past studies have shown that increases in the amount of Nicotine content of a cigarette are accompanied by an increase in the amount of Carbon. Please see the attached file.
Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. Y = 130 - 20 X Based on the above estimated regression equation, if the price is increased by 2 units, then demand is expected to decrease by 90 units i
Please see the attached file.
13. The following data are prices for custom homes comparing square feet (given in hundreds) and price (in thousands). Square Feet Price 26 259 27 274 32 315 29 296 29 325 34 380 32 359 40 523 22 215
A regression model relating x, number of sales persons at a branch office, to y, annual sales at the office ($1000s), has been developed. The computer output from a regression analysis of the data follows. The regression equation is Y = 80.0 + 50.0X Predictor Coef Stdev t-ratio Constant 80.0 11.333 7.
Please see the attached file. You want to develop a model to predict the assessed value of houses, based on heating area. A sample of 15 single-family houses is selected in a city. The assessed value (in thousand of dollars) and the heating area of the houses (in thousands of square feet) are recorded, with the following res
1. Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indi-cates the number of client contacts last month, and th
Consider the following regression model: ? D = percent change in DJIA (Dow Jones Ind. Avg.); ? O = per barrel price of oil; ? I = interest rates (in real number percentages: 6%, etc); ? E = corporate earnings growth rate; ? G = GDP growth rate. ? R2 = 0.8500 ? F = 24 ? F(Se) = 1.0 ? D = 2.0 - 3.0I + 1.5E - 1
You are the general marketing manager of Ford Motor company. The CEO of the company asked you to assess the viability of producing alternative fuel automobiles (ex, ethanol). What types of forecasting techniques would you use to forecast sales? Should you determine that regression analysis may be beneficial in addressing this qu
Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.
3. Bi-lo Appliance Stores has outlets in several large metropolitan areas. The general sales manager plans to air a commercial for a digital camera on selected local TV stations prior to a sale starting on Saturday and ending Sunday. She plans to get the information for Saturday-Sunday digital camera sales at the various outlets
An area of concern for the committee is that pay rates are linked in large measure to seniority. The committee realizes the relationship can't be perfect, other factors such as merit and contribution to the company are also used to determine pay. The committee thinks if there is a strong relationship that could be used to induce
Tree diagram: A. Perform a decision tree analysis of Steeley Associates' decision situation using expected value, and indicate the appropriate decision with these criteria. B. Indicate the decision you would make, and explain your reasons.
Case Problem #2 Steeley Associates, Inc. a property development firm, property development firm purchased an old house near the town square in Concord Falls, where State University is located. The old house was built in the mid-1800s, and Steeley Associates restored it. For almost a decade, Steeley has leased it to the univer
Please see attachment! Use the data from Exercise #12.3 below. (a) Plot a scatter diagram, (b) Show the equation on the plot using the trendline option of Excel, (c) State the value of the slope, and (d) State the value of the intercept. Use the data from Exercise #14.1 (see below) and (a) Plot a scatter dia
A highway employee performed a regression analysis of the relationship between the number of construction work-zone fatalities and the number of unemployed people in a state. The regression equation is Fatalities _ 12.7 _ 0.000114 (Unemp). Some additional output is: Predictor Coef SE Coef T P Constant 12.726 8.115 1.57 0.134
What is the "up-and-down" variation, the periods of prosperity followed by recession that occurs over extended periods of time?
Need help on some questions and answers. What is the "up-and-down" variation, the periods of prosperity followed by recession that occurs over extended periods of time? a. secular trend b. seasonal variation c. cyclical variation d. irregular variation What is the variation within a year called? This is variation, s
1. I would like to a use the regression equation: Y'= a + bX Please present the calculations and results and ANOVA Graphs using a scatter diagram
Please see the attached file. 15.2 Teenagers make up a large percentage of the market for clothing. Below are data on running shoe ownership in four world regions (excluding China). Research question: At α = .01, does this sample show that teenage running shoe ownership depends on world region? (See J. Paul Peter and Jer