Statistics for Business and Economics
8th Edition
ISBN: 9780132745659
Author: Paul Newbold, William Carlson, Betty Thorne
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Question
Chapter 1.2, Problem 8E
(a)
To determine
The example of categorical variable with ordinal response.
(b)
To determine
The example of categorical variable with nominal response.
(c)
To determine
The example of numerical variable with continuous response.
(d)
To determine
The example of numerical variable with discrete response.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the
house. The dependent variable is the selling price of the house, the first independent variable (x1) is the square footage, the second independent variable (x2) is the
number of bedrooms, and the third independent variable (x3) is the age of the house.
Effects on Selling Price of Houses
Square Feet
Number of Bedrooms Age Selling Price
2756
4
14
310300
2721
4
12
291500
2666
4
8
281100
2102
4
7
265600
1880
3
7
237500
1829
3
6
184600
1599
3
4
160800
1422
3
3
132600
1199
3
3
130500
Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places.
Copy Data
O Macmillan Learning
A study is designed to examine the relationship between employees' job satisfaction and the amount of sleep they get. Think
about creating a data set for this study. Assume that job satisfaction is measured by a scale of 1 (very dissatisfied) to 5
(very satisfied).
Cases:
Label Variable(s):
Quantitative Variable(s):
Categorical Variable(s):
Explanatory Variable(s):
Response Variable(s):
Employee's name
Answer Bank
Job satisfaction
Employees
Amount of sleep
Data table
Two Stage Least Squares Estimates
of the Demand for Cigarettes Using Panel Data for 48 U.S. States
Dependent variable: In
Regressor
cigarettes
i, 1995
In
(pi $)-In
pcigarettes
i, 1995
In (Inci, 1995) - In (Inci, 1985)
Intercept
cigarettes
Instrumental variable(s)
First-stage F-statistic
Overidentifying restrictions J-test
and p-value
- In
cigrattes
i, 1985
Q
(1)
-0.94**
(0.21)
0.53
(0.34)
-0.12
(0.07)
Sales tax
33.70
Print
(2)
-1.34**
(0.23)
0.43
(0.30)
-0.02
(0.07)
Cigarette-specific tax
107.20
(3)
- 1.20**
(0.20)
0.46
(0.31)
-0.05
(0.06)
Done
Both sales tax
cigarette-specif
These regressions were estimated using data for 48 U.S. states (48 observations on the 10-year differenc
data are described in Appendix 12.1. The J-test of overidentifying restrictions is described in Key Concept
p-value is given in parentheses), and the first-stage F-statistic is described in Key Concept 12.5. Individual
coefficients are statistically significant at the *5% level or **1% significance…
Chapter 1 Solutions
Statistics for Business and Economics
Ch. 1.2 - Prob. 1ECh. 1.2 - Prob. 2ECh. 1.2 - Prob. 3ECh. 1.2 - Prob. 4ECh. 1.2 - Prob. 5ECh. 1.2 - Prob. 6ECh. 1.2 - Prob. 7ECh. 1.2 - Prob. 8ECh. 1.3 - Prob. 9ECh. 1.3 - Prob. 10E
Ch. 1.3 - Prob. 11ECh. 1.3 - Prob. 12ECh. 1.3 - Prob. 13ECh. 1.3 - Prob. 14ECh. 1.3 - Prob. 15ECh. 1.3 - Prob. 16ECh. 1.3 - Prob. 17ECh. 1.3 - Prob. 18ECh. 1.3 - Prob. 19ECh. 1.4 - Prob. 20ECh. 1.4 - Prob. 21ECh. 1.4 - Prob. 22ECh. 1.4 - Prob. 23ECh. 1.4 - Prob. 24ECh. 1.4 - Prob. 25ECh. 1.4 - Prob. 26ECh. 1.4 - Prob. 27ECh. 1.4 - Prob. 28ECh. 1.4 - Prob. 29ECh. 1.5 - Prob. 30ECh. 1.5 - Prob. 31ECh. 1.5 - Prob. 32ECh. 1.5 - Prob. 33ECh. 1.5 - Prob. 34ECh. 1.5 - Prob. 35ECh. 1.5 - Prob. 36ECh. 1.5 - Prob. 37ECh. 1.5 - Prob. 38ECh. 1.5 - Prob. 39ECh. 1.5 - Prob. 40ECh. 1.5 - Prob. 41ECh. 1.5 - Prob. 42ECh. 1.5 - Prob. 43ECh. 1.5 - Prob. 44ECh. 1.5 - Sales revenue totals (in dollars) by day of the...Ch. 1.5 - Prob. 46ECh. 1.6 - Prob. 47ECh. 1.6 - Prob. 48ECh. 1.6 - Prob. 49ECh. 1.6 - Prob. 50ECh. 1 - Prob. 51ECh. 1 - Prob. 52ECh. 1 - Prob. 53ECh. 1 - Prob. 54ECh. 1 - Prob. 55ECh. 1 - Prob. 56ECh. 1 - Prob. 57ECh. 1 - Prob. 58ECh. 1 - Prob. 59ECh. 1 - Prob. 60ECh. 1 - Prob. 61ECh. 1 - Prob. 62ECh. 1 - Prob. 63ECh. 1 - Prob. 64ECh. 1 - Prob. 65ECh. 1 - Prob. 66ECh. 1 - Prob. 67ECh. 1 - Prob. 68ECh. 1 - Prob. 69ECh. 1 - Prob. 71ECh. 1 - Prob. 72ECh. 1 - Prob. 73ECh. 1 - Prob. 74E
Knowledge Booster
Similar questions
- Suppose researchers use observational data to study the effect of class size and teacher experience on student score. Which of the following is a confounding variable? Student score 0000 Family income Class size Teacher experiencearrow_forwardYpsilanti Market Research conducted a survey to find out whether people who earn more money purchase more expensive goods. The following graph indicates the relationship between income the survey subjects earned and the price of the home that they purchased. PRICE (Thousands of dollars per home) 500 450 400 350 300 250 200 150 100 50 L 0 10 20 30 40 50 60 70 80 INCOME (Thousands of dollars per year) 90 100arrow_forwardVariables typically included in a multivariate demand function (other than the price and quantity of the item the demand function represents) are consumer tastes and preferences, the number of buyers, spendable (disposable) income, prices of substitute goods, prices of complementary goods, advertising expenditures, weather, and expectations. Recalling that the price of the item being considered is placed on the vertical axis, and the quantity on the horizontal axis, the other variables are termed demand shifters. Please answer the following questions about the affect changes in other variables might have on the demand for the item. These changes will either cause demand to increase (shift right) or decrease (shift left). Use either word as applicable, for the short answer. If the price of a good increases because the demand for it increases, What would you expect the demand for its complement to do? If the demand for coffee beans increases, then what is likely to happen…arrow_forward
- Suppose that you had data on the amount of pollution in London every year. Write down the regression equation that you would need to estimate to measure the effect of ULEZ on pollution. Describe carefully what the dependent variable, the independent variable, the unit of observation (time or location), and the main coefficient of interest are. What control variables do you think should be included in this regression?arrow_forwardWhat is the difference between an unbiased estimator and a consistentestimator?arrow_forwardThe following data was collected to explore how a student's age and GPA affect the number of parking tickets they receive in a given year. The dependent variable is the number of parking tickets, the first independent variable (1) is the student's age, and the second independent variable (x2) is the student's GPA. Effects on Number of Parking Tickets Age GPA Number of Tickets 17 2 1 17 2 2 18 2 4 20 2 5 20 3 5 22 3 6 233 22 3 6 3 7 25 4 7 Copy Data Step 2 of 2: Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant. Answer How to enter your answer (opens in new window) Selecting a checkbox will replace the entered answer…arrow_forward
- Using the data in the worksheet "HoneyData" create a correlation table using the Analysis Toolpack in Excel. Using this information, answer the following questions and round your numeric answer to 2 decimal places. The correlation between Production and Average Price is: This means that honey Production and Average Price are negatively/positively correlated. An Increase in Production is associated with an increase/decrease in Average Prices.arrow_forwardIn this exercise, you will investigate the relationship between earnings and height. These data are taken from the US National Health Interview Survey for 1994. Download the data from the table by clicking the download table icon . A detailed description of the variables used in the dataset is available here LOADING... . Use a statistical package of your choice to answer the following questions. Earnings and…arrow_forwardA researcher wants to study about the behaviours of postgraduate students in Australia in mobile phone usage. One of the goals of the study is to analyse whether there is a relationship between the type of apps that the students use the most and the degree they are studying. What is the most suitable graph to see the relationship described above? Why?arrow_forward
- The following equation relates spending on medical care in thousands of dollars on age in years: medspend = 5.3 + 1.2age If, instead, we change the scale of medicare care spending to dollars, the slope coefficient will be: 120 0.0012 1200 0.012arrow_forwardCafé Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values: Price $2.50 $3.60 $1.90 $4.10 $3.10 $4.10 Number Sold 760 515 980 245 325 490 Using simple linear regression and given that the price per cup is $1.85, the forecasted demand for mocha latte coffees will be cups (enter your response rounded to one decimal place).arrow_forward团 jarb Hamed - A Find - eac Replace A Select - Editing Story: An E-Commerce portal has collected data regarding the customer activity on the website, app, and purchase portal. The portal management wanted to study the relationship between customers' length of Memberships and the yearly money amount spent by the customer buying stuff on their portal (The last two columns in the datasheet). Unfortunately, some information regarding some customers is missing e.g. Length of Membership. (A.) You have three approaches that needed to be tackled: 1) Fill the missing data using zeros 2) Fill the missing data using the mean of their column 3) Fill the missing data using the median of their column After trying each of them you need to study the effect of your new data proposition on the correlation between "Length of Membership" and "Yearly Amount Spent (B.) Using Principal Components Analysis (PCA), Reduce the number of independent variables to only two(use any library you want for PCA) Data:…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Managerial Economics: Applications, Strategies an...EconomicsISBN:9781305506381Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. HarrisPublisher:Cengage Learning
Managerial Economics: Applications, Strategies an...
Economics
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:Cengage Learning