EP BASIC BUS.STATS-ACCESS (18 WEEKS)
14th Edition
ISBN: 9780135989005
Author: BERENSON
Publisher: PEARSON CO
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Chapter 14, Problem 8PS
a.
To determine
Determine the multiple regression equation for the givenscenario.
b.
To determine
Interpret the meaning of slopes.
c.
To determine
Explain why regression coefficient,
d.
To determine
Predict the mean fair market value when land area and age are given.
e.
To determine
Construct
f.
To determine
Construct
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Find the degrees of freedom in a regression model with an intercept term that has 88 observations and 7 explanatory variables.
Nassau County is located approximately 25 miles east of New York City. The accompanying data include the fair market value (in thousands of dollars), land area of the property in acres, and age, in years, for a sample of 20 single-family homes located in
Glen Cove, a small city in Nassau County. Develop a multiple linear regression model to predict the fair market value based on land area of the property and age, in years. Complete parts (a) through (f).
Click the icon to view the data table.
a. State the multiple regression equation. Let X1; represent the land area of the property in acres and let X2 represent age, in years.
Ý; = 458.4 + ( 421.7) ×1 + ( – 1.8) X21
-
(Round to one decimal place as needed.)
b. Interpret the meaning of the slopes, b, and b2, in this problem. Choose the correct answer below.
O A. For a given age, each increase of 1 acre in land area is estimated to result in an increase in fair market value by b, dollars. For a given land area, each increase in one year…
Q1) A real estate consultant is considering developing a series of price models for
residential houses in different areas of the province of Ontario, in Canada. The
dataset, provided by the Windsor and Essex County Board, covers residential home
sales in Windsor. To develop the model, the consultant performs a linear regression to
estimate the price (in Canadian dollars) as a linear function of the size of the
apartment (in square feet) and obtains the following Excel result.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
0.53580413
0.28708607
0.28577556
41101.9362
546
ANOVA
df
MS
Significance F
1 3.70082E+11 3.7008E+11 219.065461 6.74643E-42
Regression
Residual
Total
544 9.19017E+11 1689369158
545
1.2891E+12
Coefficients Standard Error
62171.5874 4537.036582 13.7031268 6.2969E-37 53259.33066 71083.8441
t Stat
P-value
Lower 95%
Upper 95%
Intercept
LOTSIZE
12.0187669
0.81203165 14.8008601 6.7464E-42 10.42366523 13.6138685
a) Write…
Chapter 14 Solutions
EP BASIC BUS.STATS-ACCESS (18 WEEKS)
Ch. 14 - For this problem, use the following multiple...Ch. 14 - For this problem, use the following multiple...Ch. 14 - A nonprofit analyst seeks to determine which...Ch. 14 - Profitability remains a challenge for banks and...Ch. 14 - The production of wine is a multibillion-dollar...Ch. 14 - Human resource managers face the business problem...Ch. 14 - Prob. 7PSCh. 14 - Prob. 8PSCh. 14 - The following ANOVA summary table is for a...Ch. 14 - The following ANOVA summary table is for a...
Ch. 14 - A financial analyst engaged in business valuation...Ch. 14 - In Problem 14.3 on page 541, you predicted...Ch. 14 - In Problem 14.5 on page 542, you used the...Ch. 14 - In Problem 14.4 on page 541, you used efficiency...Ch. 14 - In Problem 14.7 on page 542, you used the weekly...Ch. 14 - Prob. 16PSCh. 14 - Prob. 17PSCh. 14 - Prob. 18PSCh. 14 - In Problem 14.5 on page 542, you used the...Ch. 14 - Prob. 20PSCh. 14 - Prob. 21PSCh. 14 - Prob. 22PSCh. 14 - Prob. 23PSCh. 14 - Prob. 24PSCh. 14 - In Problem 14.3 on page 541, you predicted...Ch. 14 - In Problem on page 541, you used efficiency ratio...Ch. 14 - Prob. 27PSCh. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - Prob. 29PSCh. 14 - Prob. 30PSCh. 14 - The following is the ANOVA summary table for a...Ch. 14 - The following is the ANOVA summary table for a...Ch. 14 - In Problem 14.5 on page 542, you used alcohol...Ch. 14 - In Problem 14.4 on page 541, you used efficiency...Ch. 14 - Prob. 35PSCh. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - Prob. 37PSCh. 14 - Suppose X1 is a numerical variable and X2 is a...Ch. 14 - The chair of the accounting department plans to...Ch. 14 - A real estate association in a suburban community...Ch. 14 - In Problem 14.5 on page 542, you developed a...Ch. 14 - In mining engineering, holes are often drilled...Ch. 14 - The owner of a moving company typically has his...Ch. 14 - Prob. 44PSCh. 14 - Zagat’s publishes restaurant rating for various...Ch. 14 - In Problem 14.6 on page 542, you used full-time...Ch. 14 - In Problem 14.5 on page 542, the percentage of...Ch. 14 - Prob. 48PSCh. 14 - The director of a training program for a large...Ch. 14 - Prob. 50PSCh. 14 - Prob. 51PSCh. 14 - Prob. 52PSCh. 14 - Prob. 53PSCh. 14 - Prob. 54PSCh. 14 - Prob. 55PSCh. 14 - Prob. 56PSCh. 14 - Prob. 57PSCh. 14 - An automotive insurance company wants to predict...Ch. 14 - A marketing manager wants to predict customer with...Ch. 14 - A local supermarket manager wants to use two...Ch. 14 - Prob. 61PSCh. 14 - Prob. 62PSCh. 14 - Prob. 63PSCh. 14 - Prob. 64PSCh. 14 - Prob. 65PSCh. 14 - Prob. 66PSCh. 14 - Prob. 67PSCh. 14 - Prob. 68PSCh. 14 - Prob. 69PSCh. 14 - Prob. 70PSCh. 14 - Prob. 71PSCh. 14 - The owner of a moving company typically has his...Ch. 14 - Professional basketball has truly become a sport...Ch. 14 - A sample of 61 house recently listed for sale in...Ch. 14 - Measuring the height of a California redwood tree...Ch. 14 - A sample of 61 houses recently listed for sale in...Ch. 14 - Prob. 77PSCh. 14 - Referring to Problem 14.77, Suppose that an...Ch. 14 - Prob. 79PSCh. 14 - Prob. 80PSCh. 14 - Prob. 81PSCh. 14 - Prob. 82PSCh. 14 - Prob. 83PS
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- Does Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forwardFind the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forward
- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardFind the regression line of the points: (12.7, 18.7), (9.1, 17.2), (15.3, 14.5), (19.5, 12.9)arrow_forwardExplain why it is not a good idea to exclude an intercept, b0 , from any linear regression model?arrow_forward
- A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+BOIL+YEXP+8FDI Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports (S000's) and FDI = annual foreign direct investment (S000's). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 ** s = 2.45 R-sq = 96.3% R-sq (adj) = 95.3% Analysis of Variance Source DF MS F Regression 3 1991.31 663.77 ? ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values ***, ***', ?'and ??' d) Hence test whether ß is significant. Give reasons for your answer. e) Perform…arrow_forwardA researcher collected statistics on the sales amount of a product in 120 different markets and the advertising budgets used in TV, radio and newspaper media channels for each of these markets. The sales amount are expressed in 1000 units, and the budgets are expressed in 1000$. The researcher wants to create a simple linear regression model by choosing one among the TV, radio and newspaper advertising budgets to explain the amount of sales. Accordingly, answer the following question by using the data in the "Regression Data Set" document in the appendix. 1) a) In your opinion, which variable should this researcher choose as an independent variable to the simple regression model? Explain your decision by providing its statistical basis.arrow_forwardA researcher collected statistics on the sales amount of a product in 120 different markets and the advertising budgets used in TV, radio and newspaper media channels for each of these markets. The sales amount are expressed in 1000 units, and the budgets are expressed in 1000$. The researcher wants to create a simple linear regression model by choosing one among the TV, radio and newspaper advertising budgets to explain the amount of sales. Accordingly, answer the following question by using the data in the "Regression Data Set" document in the appendix.1) b) In your opinion, which variable should this researcher choose as an independent variable to the simple regression model? Establish the simple linear regression model using the argument of your choice and write the equation for the model. Interpret b0 and b1.1) c) Test whether there is a statistically significant and linear relationship between the independent variable and the dependent variable by establishing the relevant…arrow_forward
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