Statistics: The Art and Science of Learning from Data (4th Edition)
4th Edition
ISBN: 9780321997838
Author: Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: PEARSON
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Chapter 13, Problem 81CP
To determine
Explain the reason that the variable suggested to represent the religious affiliation of a person is inappropriate.
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Q.1.2
Match the definition in column X with the correct term in column Y.
Two marks will be awarded for each correct answer.
(20)
COLUMN X
Q.1.2.1
COLUMN Y
Condenses sample data into a few summary
A.
Statistics
measures
Q.1.2.2
The collection of all possible observations that
exist for the random variable under study.
B.
Descriptive statistics
Q.1.2.3
Describes a characteristic of a sample.
C.
Ordinal-scaled data
Q.1.2.4
The actual values or outcomes are recorded
on a random variable.
D.
Inferential statistics
0.1.2.5
Categorical data, where the categories have an
implied ranking.
E.
Data
Q.1.2.6
A set of mathematically based tools &
techniques that transform raw data into
F.
Statistical modelling
information to support effective decision-
making.
45
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The following table indicates the unit prices (in Rands) and quantities of three consumer products
to be held in a supermarket warehouse in Lenasia over the time period from April to July 2025.
APRIL 2025
JULY 2025
PRODUCT
Unit Price (po)
Quantity (q0))
Unit Price (p₁)
Quantity (q1)
Mineral Water
R23.70
403
R25.70
423
H&S Shampoo
R77.00
922
R79.40
899
Toilet Paper
R106.50
725
R104.70
730
The Independent Institute of Education (Pty) Ltd 2025
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QUAT6221wA1
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The following table indicates the unit prices (in Rands) and quantities of three meals sold every year
by a small restaurant over the years 2023 and 2025.
2023
2025
MEAL
Unit Price (po) Quantity (q0))
Unit Price (P₁)
Quantity (q₁)
Lasagne
R125
1055
R145
1125
Pizza
R110
2115
R130
2195
Pasta
R95
1950
R120
2250
Q.2.1
Using 2023 as the base year, compute the individual price relatives in 2025 for (10)
lasagne and pasta. Interpret each of your answers.
0.2.2
Using 2023 as the base year, compute the Laspeyres price index for all of the meals (8)
for 2025. Interpret your answer.
Q.2.3
Using 2023 as the base year, compute the Paasche price index for all of the meals (7)
for 2025. Interpret your answer.
Q Search
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Chapter 13 Solutions
Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 13.1 - Predicting weight For a study of female college...Ch. 13.1 - Prob. 2PBCh. 13.1 - Predicting college GPA For all students at Walden...Ch. 13.1 - Prob. 4PBCh. 13.1 - Does more education cause more crime? The FL Crime...Ch. 13.1 - Crime rate and income Refer to the previous...Ch. 13.1 - The economics of golf The earnings of a PGA Tour...Ch. 13.1 - Prob. 8PBCh. 13.1 - Controlling can have no effect Suppose that the...Ch. 13.1 - House selling prices Using software with the House...
Ch. 13.1 - Used cars The following data (also available from...Ch. 13.2 - Predicting sports attendance Keeneland Racetrack...Ch. 13.2 - Predicting weight Lets use multiple regression to...Ch. 13.2 - Prob. 14PBCh. 13.2 - Price of used cars For the 19 used cars listed in...Ch. 13.2 - Prob. 16PBCh. 13.2 - Softball data For the Softball data set on the...Ch. 13.2 - Slopes, correlations, and units In Example 2 on y...Ch. 13.2 - Predicting college GPA Using software with the...Ch. 13.3 - Predicting GPA For the 59 observations in the...Ch. 13.3 - Study time help GPA? Refer to the previous...Ch. 13.3 - Variability in college GPA Refer to the previous...Ch. 13.3 - Does leg press help predict body strength? Chapter...Ch. 13.3 - Prob. 24PBCh. 13.3 - Interpret strength variability Refer to the...Ch. 13.3 - Any predictive power? Refer to the previous three...Ch. 13.3 - Predicting pizza revenue Aunt Ermas Pizza...Ch. 13.3 - Prob. 28PBCh. 13.3 - Mental health again Refer to the previous...Ch. 13.3 - Prob. 30PBCh. 13.3 - House prices Use software to do further analyses...Ch. 13.4 - Body weight residuals Examples 47 used multiple...Ch. 13.4 - Strength residuals In Chapter 12, we analyzed...Ch. 13.4 - Prob. 34PBCh. 13.4 - Nonlinear effects of age Suppose you fit a...Ch. 13.4 - Prob. 36PBCh. 13.4 - Why inspect residuals? When we use multiple...Ch. 13.4 - College athletes The College Athletes data set on...Ch. 13.4 - House prices Use software with the House Selling...Ch. 13.4 - Prob. 40PBCh. 13.5 - U.S. and foreign used cars Refer to the used car...Ch. 13.5 - Prob. 42PBCh. 13.5 - Predict using house size and condition For the...Ch. 13.5 - Quality and productivity The table shows data from...Ch. 13.5 - Predicting hamburger sales A chain restaurant that...Ch. 13.5 - Prob. 46PBCh. 13.5 - House size and garage interact? Refer to the...Ch. 13.5 - Prob. 48PBCh. 13.5 - Comparing sales You own a gift shop that has a...Ch. 13.6 - Prob. 50PBCh. 13.6 - Prob. 51PBCh. 13.6 - Prob. 52PBCh. 13.6 - Prob. 53PBCh. 13.6 - Prob. 54PBCh. 13.6 - Prob. 55PBCh. 13.6 - Prob. 56PBCh. 13.6 - Prob. 57PBCh. 13.6 - Prob. 58PBCh. 13.6 - Prob. 59PBCh. 13 - House prices This chapter has considered many...Ch. 13 - Prob. 61CPCh. 13 - Prob. 62CPCh. 13 - Prob. 63CPCh. 13 - Prob. 64CPCh. 13 - Prob. 65CPCh. 13 - Prob. 66CPCh. 13 - Prob. 67CPCh. 13 - Prob. 68CPCh. 13 - Prob. 69CPCh. 13 - AIDS and AZT In a study (reported in the New York...Ch. 13 - Factors affecting first home purchase The table...Ch. 13 - Unemployment and GDP Refer to Exercise 13.67. When...Ch. 13 - Prob. 75CPCh. 13 - Prob. 76CPCh. 13 - Prob. 77CPCh. 13 - Prob. 78CPCh. 13 - Prob. 79CPCh. 13 - True or false: Slopes For data on y = college GPA,...Ch. 13 - Prob. 81CPCh. 13 - Lurking variable Give an example of three...Ch. 13 - Prob. 83CPCh. 13 - Prob. 84CPCh. 13 - Prob. 85CPCh. 13 - Logistic versus linear For binary response...Ch. 13 - Prob. 87CPCh. 13 - Prob. 88CPCh. 13 - Prob. 89CPCh. 13 - Prob. 90CPCh. 13 - Prob. 91CPCh. 13 - Prob. 92CPCh. 13 - Prob. 93CP
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- QUAI6221wA1.docx X + int.com/:w:/r/sites/TertiaryStudents/_layouts/15/Doc.aspx?sourcedoc=%7B2759DFAB-EA5E-4526-9991-9087A973B894%7 26 QUAT6221wA1 Q.1.1.8 One advantage of primary data is that: (1) It is low quality (2) It is irrelevant to the purpose at hand (3) It is time-consuming to collect (4) None of the other options Accessibility Mode Immersive R Q.1.1.9 A sample of fifteen apples is selected from an orchard. We would refer to one of these apples as: (2) ھا (1) A parameter (2) A descriptive statistic (3) A statistical model A sampling unit Q.1.1.10 Categorical data, where the categories do not have implied ranking, is referred to as: (2) Search D (2) 1+ PrtSc Insert Delete F8 F10 F11 F12 Backspace 10 ENG USarrow_forwardepoint.com/:w:/r/sites/TertiaryStudents/_layouts/15/Doc.aspx?sourcedoc=%7B2759DFAB-EA5E-4526-9991-9087A 23;24; 25 R QUAT6221WA1 Accessibility Mode DE 2025 Q.1.1.4 Data obtained from outside an organisation is referred to as: (2) 45 (1) Outside data (2) External data (3) Primary data (4) Secondary data Q.1.1.5 Amongst other disadvantages, which type of data may not be problem-specific and/or may be out of date? W (2) E (1) Ordinal scaled data (2) Ratio scaled data (3) Quantitative, continuous data (4) None of the other options Search F8 F10 PrtSc Insert F11 F12 0 + /1 Backspaarrow_forward/r/sites/TertiaryStudents/_layouts/15/Doc.aspx?sourcedoc=%7B2759DFAB-EA5E-4526-9991-9087A973B894%7D&file=Qu Q.1.1.14 QUAT6221wA1 Accessibility Mode Immersive Reader You are the CFO of a company listed on the Johannesburg Stock Exchange. The annual financial statements published by your company would be viewed by yourself as: (1) External data (2) Internal data (3) Nominal data (4) Secondary data Q.1.1.15 Data relevancy refers to the fact that data selected for analysis must be: (2) Q Search (1) Checked for errors and outliers (2) Obtained online (3) Problem specific (4) Obtained using algorithms U E (2) 100% 高 W ENG A US F10 点 F11 社 F12 PrtSc 11 + Insert Delete Backspacearrow_forward
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