Back-to-Back Relative Frequency Histograms When using histograms to compare two data sets, it is sometimes difficult to make comparisons by looking back and forth between the two histograms. A backtoback relative frequency histogram has a format that makes the comparison much easier. Instead of frequencies, we should use relative frequencies (percentages or proportions) so that the comparisons are not difficult when there are different sample sizes. Use the relative frequency distributions of the ages of Oscar-winning actresses and actors from Exercise 15 in Section 22, and complete the backtoback relative frequency histograms shown below. Then use the result to compare the two data sets.
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1
Introduction to Statistics
1-2
Statistical and Critical Thinking
1-3
Types of Data
1-4
Collecting Sample Data
1.2
Statistical and Critical Thinking
1.3
Types of Data
1.4
Collecting Sample Data
2
Summarizing and Graphing
2-2
Frequency Distributions
2-3
Histograms
2-4
Graphs That Enlighten and Graphs That Deceive
2.2
Frequency Distributions
2.3
Histograms
2.4
Graphs That Enlighten and Graphs That Deceive
3
Statistics for Describing, Exploring, and Comparing Data
3-2
Measures of Center
3-3
Measures of Variation
3-4
Measures of Relative Standing and Boxplots
3.2
Measures of Center
3.3
Measures of Variation
3.4
Measures of Relative Standing and Boxplots
4
Probability
4-2
Basic Concepts of Probability
4-3
Addition Rule
4-4
Multiplication Rule: Basics
4-5
Multiplication Rule: Complements and Conditional Probability
4-6
Counting
4.2
Basic Concepts of Probability
4.3
Addition Rule
4.4
Multiplication Rule: Basics
4.5
Multiplication Rule: Complements and Conditional Probability
4.6
Counting
4.7
Probabilities Through Simulations (on CD-ROM)
4.8
Bayes' Theorem (on CD-ROM)
5
Discrete Probability Distributions
5-2
Probability Distributions
5-3
Binomial Probability Distributions
5-4
Parameters for Binomial Distributions
5-5
Poisson Probability Distributions
5.2
Probability Distributions
5.3
Binomial Probability Distributions
5.4
Parameters for Binomial Distributions
5.5
Poisson Probability Distributions
6
Normal Probability Distributions
6-2
The Standard Normal Distribution
6-3
Applications of Normal Distributions
6-4
Sampling Distributions and Estimators
6-5
The Central Limit Theorem
6-6
Assessing Normality
6-7
Normal as Approximation to Binomial
6.2
The Standard Normal Distribution
6.3
Applications of Normal Distributions
6.4
Sampling Distributions and Estimators
6.5
The Central Limit Theorem
6.6
Assessing Normality
6.7
Normal as Approximation to Binomial
7
Estimates and Sample Sizes
7-2
Estimating a Population Proportion
7-3
Estimating a Population Mean
7-4
Estimating a Population Standard Deviation or Variance
7.2
Estimating a Population Proportion
7.3
Estimating a Population Mean
7.4
Estimating a Population Standard Deviation or Variance
8
Hypothesis Testing
8-2
Basics of Hypothesis Testing
8-3
Testing a Claim About a Proportion
8-4
Testing a Claim About a Mean
8-5
Testing a Claim About a Standard Deviation or Variance
8.2
Basics of Hypothesis Testing
8.3
Testing a Claim About a Proportion
8.4
Testing a Claim About a Mean
8.5
Testing a Claim About a Standard Deviation or Variance
9
Inferences from Two Samples
9-2
Two Proportions
9-3
Two Means: Independent Samples
9-4
Two Dependent Samples (Matched Pairs)
9-5
Two Variances or Standard Deviations
9.2
Two Proportions
9.3
Two Means: Independent Samples
9.4
Two Dependent Samples (Matched Pairs)
9.5
Two Variances or Standard Deviations
10
Correlation and Regression
10-2
Correlation
10-3
Regression
10-4
Prediction Intervals and Variation
10-5
Multiple Regression
10-6
Nonlinear Regression
10.2
Correlation
10.3
Regression
10.4
Prediction Intervals and Variation
10.5
Multiple Regression
10.6
Nonlinear Regression
11
Goodness-of-Fit and Contingency Tables
11-2
Goodness-of-Fit
11-3
Contingency Tables
11.2
Goodness-of-Fit
11.3
Contingency Tables
12
Analysis of Variance
12-2
One-Way ANOVA
12-3
Two-Way ANOVA
12.2
One-Way ANOVA
12.3
Two-Way ANOVA
13
Nonparametric Tests
13-3
Wilcoxon Signed-Ranks Test for Matched Pairs
13-4
Wilcoxon Rank-Sum Test for Two Independent Samples
13-5
Kruskal-Wallis Test
13-6
Rank Correlation
13-7
Runs Test for Randomness
13.2
Sign Test
13.2
Sign Test
13.3
Wilcoxon Signed-Ranks Test for Matched Pairs
13.4
Wilcoxon Rank-Sum Test for Two Independent Samples
13.5
Kruskal-Wallis Test
13.6
Rank Correlation
13.7
Runs Test for Randomness
14
Statistical Process Control
14-2
Control Charts for Variation and Mean
14-3
Control Charts for Attributes
14.2
Control Charts for Variation and Mean
14.3
Control Charts for Attributes
Textbook Solutions for Elementary Statistics
Chapter 2.4 Problem 3CQQ
Question
The first class described in Exercise 1 has a frequency of 51. If you know only the class limits given in Exercise 1 and the frequency of 51, can you identify the original 51 data values?
Title
Elementary Statistics 12
Author
Mario F. Triola
ISBN
9780321836960