- 2-2.1: What questions could be answered more easily by looking at the hist...
- 2-2.2: What different questions could be answered more easily by looking a...
- 2-2.3: What different questions could be answered more easily by looking a...
- 2-2.4: Are there any extremely large or extremely small data values compar...
- 2-2.5: Which graph displays these extremes the best?
- 2-2.6: Is the distribution skewed?
- 2-2.1: Do Students Need Summer Development? For 108 randomly selected coll...
- 2-2.2: Number of College Faculty The number of faculty listed for a variet...
- 2-2.3: Counties, Divisions, or Parishes for 50 States The number of counti...
- 2-2.4: NFL Salaries The salaries (in millions of dollars) for 31 NFL teams...
- 2-2.5: Automobile Fuel Efficiency Thirty automobiles were tested for fuel ...
- 2-2.6: Construct a frequency histogram, a frequency polygon, and an ogive ...
- 2-2.7: Air Quality Standards The number of days that selected U.S. metropo...
- 2-2.8: How Quick Are Dogs? In a study of reaction times of dogs to a speci...
- 2-2.9: Quality of Health Care The scores of health care quality as calcula...
- 2-2.10: Making the Grade The frequency distributions shown indicate the per...
- 2-2.11: Construct a histogram, a frequency polygon, and an ogive for the da...
- 2-2.12: For the data in Exercise 18 in Section 21, construct a histogram fo...
- 2-2.13: For the data in Exercise 1 in this section, construct a histogram, ...
- 2-2.14: For the data for 2003 in Exercise 4 in this section, construct a hi...
- 2-2.15: Cereal Calories The number of calories per serving for selected rea...
- 2-2.16: Protein Grams in Fast Food The amount of protein (in grams) for a v...
- 2-2.17: For the data for year 2003 in Exercise 7 in this section, construct...
- 2-2.18: How Quick Are Older Dogs? The animal trainer in Exercise 8 in this ...
- 2-2.19: Using the histogram shown here, do the following. Class boundaries ...
- 2-2.20: Using the results from Exercise 19, answer these questions. a. How ...
Solutions for Chapter 2-2: Frequency Distributions and Graphs
Full solutions for Elementary Statistics: A Step by Step Approach | 7th Edition
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).
Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
Central limit theorem
The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.
The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.
The mean of the conditional probability distribution of a random variable.
Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.
Defects-per-unit control chart
See U chart
Another name for a probability density function
A probability distribution for a discrete random variable
Discrete random variable
A random variable with a inite (or countably ininite) range.
The amount of variability exhibited by data
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.
Any test of signiicance involving the F distribution. The most common F-tests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.
Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.