decision-making 11th edition by ken black all chapters
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,table of contents
1 introduction to statistics and business analytics
2 visualizing data with charts and graphs
3 descriptive statistics
4 probability
5 discrete distributions
6 continuous distributions
7 sampling and sampling distributions
8 statistical inference: estimation for single populations
9 statistical inference: hypothesis testing for single populations
10 statistical inferences about two populations
11 analysis of variance and design of experiments
12 simple regression analysis and correlation
13 multiple regression analysis
14 building multiple regression models
15 time-series forecasting and index numbers
16 analysis of categorical data
17 nonparametric statistics
18 statistical quality control
19 decision analysis
, file: ch01, chapter 1: introduction to statistics
true/false
virtually all areas of business use statistics in decision making. ANSWER: true
response: see section 1.1, statistics in business
difficulty: easy
learning objective: 1.1: list quantitative and graphical examples of statistics within a business context.
statistics can be used to predict the business future. ANSWER: true
response: see section 1.1, statistics in business
difficulty: easy
learning objective: 1.1: list quantitative and graphical examples of statistics within a business context.
statistics are used to market vitamins. ANSWER: true
response: see section 1.1, statistics in business
difficulty: easy
learning objective: 1.1: list quantitative and graphical examples of statistics within a business context.
a list of final grades in an introductory class in business is an example of statistics ANSWER: false
response: see section 1.1, statistics in business
difficulty: easy
learning objective: 1.1: list quantitative and graphical examples of statistics within a business context.
the complete collection of all entities under study is called the sample. ANSWER: false
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
a portion or subset of the entities under study is called the statistic. ANSWER: false
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
,a descriptive measure of the population is called a parameter. ANSWER: true
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
a census is the process of gathering data on all the entities in the population. ANSWER: true
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
statistics is commonly divided into two branches called descriptive statistics and summary statistics. ANSWER: false
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
a descriptive measure of the sample is called a statistic. ANSWER: true
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
1. gathering data from a sample to reach conclusions about the population from which the sample
was drawn is called descriptive statistics.
ANSWER: false
response: see section 1.2, basic statistical concepts
difficulty: medium
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.
2. calculation of population parameters is usually either impossible or excessively time consuming and
costly.
ANSWER: true
response: see section 1.2, basic statistical concepts
difficulty: easy
learning objective: 1.2: define important statistical terms, including population, sample, and
parameter, as they relate to descriptive and inferential statistics.