See attached files. From Statistics for Managers Using Microsoft® Excel, Fifth Edition: SH13.3 a. Analyze the data and develop a regression model to predict the mean number of new subscriptions for a month, based on the number of hours spent on telemarketing for new subscriptions. b. If you expect to spend 1,200 hour
See attached files. You are to use linear (single) regression only! The setting: Imagine you are a real estate investor presented with a regression analysis of home sales in the neighborhood of one of your investment properties. Unfortunately, the report stops short of making the decision for you. Given the data as present
In their article, "The Demand for Coffee in the United States: 1963-1977" (Quarterly Review of Economics and Business, Summer 1980, pp. 36-50), Huang, Siegfried, and Zardoshty estimated the following regression equation using quarterly data for the 58 quarters running from the first quarter of 1963 through the second quarter of
John is an avid fisherman and wants to know if there is a correlation between the amount of time he spends fishing and the amount of fish he catches. He decided to keep track of the time he spent at the lake and the amount of fish he caught. The results were as follows: Hours at lake 2 3 2 1 4 5 Number of fis
Costs for recently constructed buildings in your city are as follows: building sq ft cost of Building ($k) 12000 510 14000 565 15000 610 16000 650 18000
1. The league of American Theatres and producers, Inc, collects a variety of statistics for Broadway plays, such as gross revenue, playing time, and number of new productions. The following data show the season attendance ( in millions) for Broadway shows from 1990 to 2001 ( the world almanac 2002) Season Attendance (in milli
53. The following data show the retail price for 12 randomly selected laptop computers along with their corresponding processor speeds in gigahertz. Computer Speed Price Computer Speed Price 1 2.0 2,689 7 2.0 2,929 2 1.6 1,229 8 1.6 1,849 3 1.6 1,419 9 2.0 2,819 4 1.8 2,589 10 1.6 2,669 5 2.0 2,849 11 1.0 1,249 6 1.2 1
A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n=15 college students. The SAT scores have a mean of M=580 with SS=22,400, and the GPAs have a mean of 3.10 with SS=1.26, and SP=84. a. Find the regression equation for predicting GPA from SAT scores. b. What percentage of the variance
34. In a manufacturing process a random sample of 9 bolts manufactured has a mean length of 3 inches with a variance of 0.09. What is the 90% confidence interval for the true mean length of the bolt? A) 2.8355 to 3.1645 inches B) 2.5065 to 3.4935 inches C) 2.4420 to 3.5580 inches D) 2.8140 to 3.8160 inches E) 2.9442
See data file attached. Use the numerical data from the baseball data set (attached). For this assignment, you must have a hypothesis and have at least one independent variable (x) and the dependent variable (y) measured at the interval level. The assignment does not specify the type of regression used, so either bivariate or
35. A regional commuter airline selected a random sample of 25 flights and found that the correlation between the number of passengers and the total weight, in pounds, of luggage stored in the luggage compartment is 0.94. Using the .05 significance level, can we conclude that there is a positive association between the two vari
Multiple Regression Analysis | | The company has been able to determine that its sales in dollars depends on the advertising and the number of vendors and is therefore used data from previous years to forecast the potential sales for the year 2010. Y X1 ($000) X2($000) | Year Sales Advertising Salesman | 2003 $10 $ 1 1
Simple Regression Analysis | | A company is interested to know what the potential sales in units for 2009. To make this forecast the company uses information from previous years which is given below: Y X | Year Sales ($000) Advertising ($000) | 2002 $8 $1 | 2003 $12 $2 | 2004 $18 $ 3 | 2005 $20 $
See attached file for data. There is debate within the production planning management team as to which forecasting technique to use. The team members want to test to see which method would be more accurate. They have assigned the new planning director to assess which of the following forecasting techniques would have been mor
Choose any two sets of data. Perform linear regression and hypothesis test on the data. Interpret the results. [please refer to the attachment for details]
Explained and unexplained variation and the least-squares regression line Bivariate data obtained for the paired variables and are shown below, in the table labelled "Sample data." These data are plotted in the scatter plot in Figure 1, which also displays the least-squares regression line for the data. The equation for this
The relationship described below can be modeled using an equation. Identify the variables and write an equation to solve the questions below. (a) Write an equation to calculate the fees F when the number of credits n is given? (b) Use this equation from part (a) to calculate the fee for 17 credits. No. of Credits Fees
See attached data set. Prepare a report using Excel as your processing tool to process three simple regression analyses. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data
An electric utility wishes to examine the relationship between temperature and electricity use in its service region during the summer months. The bivariate data below give the maximum temperature (denoted by x, in degrees Fahrenheit) and the electricity use (denoted by ,y in thousands of kilowatt hours) for a random sample of f
See attached data set file. 1. Develop one research question and formulate a hypothesis which may be tested with linear regression analysis 2. Perform a regression hypothesis test on the data. Include your raw data tables and the results of your computations, using graphical and tabular methods of displaying data and re
Once we start to think about it, regression is useful in many different situations. Give an example of how you might use regression analysis in your work. As part of your answer give the model you would use and explain why you chose the specific independent variables given in your model. I own my own janitorial company.
32) Two models were proposed for a simple regression of tree height on bark thickness, Model A: Height' = 7.8*Bark + 37 and Model B: Height' = 8*Bark + 35. Using the information and calculations below, which model is best? Model A: Height' = 7.8*Bark + 37 Tree ID Height (feet) Bark Thickness (millimeters) Predicted Hei
Instructions: ? Write the regression equation ? What does R-squared value tell you? ? What meaning does intercept have? ? Which is warmer, a day with rain or a day without? ? Is KIAH_Precip a good predictor? ? Describe fit of regression It might be supposed that rainy days would tend to be cooler than
Instructions: ? Write the regression equation ? State degrees of freedom and compute critical value ? Conclusion about slope ? Interpret confidence limits for slope ? Verify that F = square of t ? Describe fit of regression It might be expected that baseball teams with better batting averages also sco
Question 1: A manufacturing company designed an experiment to determine whether the number of days necessary to develop a new product depends on whether the development processes were performed sequentially or simultaneously (the method of development). Because the duration of development would depend on whether the new produ
Think of a case in which regression analysis was used, but not properly. For instance, discuss situations in which regression analysis is not appropriate and does not add useful information to our understanding of a set of data.
A. What terms describe the fit of a regression equation to the data? What is the practical use of the regression equation in the real world? Explain with some examples. b. How would you explain the meaning of the correlation coefficient (r)? How or why it is a useful concept in real life? Explain with some examples. c. Wha
The sales, in billions of dollars, of Keller Overhead Door, Inc. for 1995 to 2000 are: Year Sales Year Sales 1996 7.45 1998 7.94 1996 7.83 1999 7.76 1997 8.07 2000 7.90 Use the trend equation to calculate the points for 1997 and 1999. Plot them on the graph and draw the regression line. Estimate the net sales for
1.A random sample of 48 days taken at a large hospital shows that an average of 38 patients was treated in the emergency room per day. The standard deviation of the population is 4. Find the 99% confidence interval of the mean number of ER patients treated each day at the hospital. 2.Using the same information as in ques
[Data attached] 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. Data for a sample of 25 apartments in a particular neighborhood are provided in the attached excel spreadsheet. 1. At the .05 level of