samedi 2 février 2019

MyLab Statistics for Statistical Reasoning -- Student Access Kit Bank Test Questions

MyLab Statistics for Statistical Reasoning -- Student Access Kit

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Table of Contents

Curriculum Overview

Before the Semester Begins: Suggestions for Prep Week

 

Lesson 1: Introduction to Statistics

1.A: Birth Dates and Personality Traits

1.B: Our Learning Community

1.C: Statistical Investigations

1.D: The Statistical Analysis Process

1.E: Types of Statistical Studies and Scope of Conclusions

 

Lesson 2: Sampling

2.A: Collecting Data by Sampling

2.B: Random Sampling

2.C: Other Sampling Methods (Optional)

2.D: Sources of Bias in Sampling

 

Lesson 3: Experiments

3.A: Planning an Experiment

3.B: Random Assignment

3.C: Control Groups and Placebos

3.D: Drawing Conclusions from Statistical Studies

3.E: Forming Effective Study Groups

 

Lesson 4: Univariate Data Displays and Measures of Center

4.A: Dotplots for Quantitative Data

4.B: Constructing Histograms for Quantitative Data

4.C: Weight Gain

4.D: Dotplots, Histograms, and Distributions

 

Lesson 5: Variability

5.A: Variability Relative to the Mean

5.B: Boxplots

5.C: The Modified Boxplot

5.D: Do the Parties Differ?

 

Lesson 6: Scatterplots and Correlation

6.A: Introduction to Two-Variable Relationships

6.B: Direction and Strength of the Relationship

6.C: Correlation Coefficient

6.D: Correlation and Cause-and-Effect Conclusions

 

Lesson 7: Lines of Best Fit

7.A: Using Lines to Make Predictions

7.B: Exploring Lines of Best Fit

7.C: Least Squares Regression (LSR) Line

7.D: Impact of Outliers on Correlations and Regression

 

Lesson 8: Least Squares Regression Line

8.A: Investigating the Numbers in a Line’s Equation

8.B: Building the LSR Line’s Equation (Optional)

8.C: Determining If a Line Is a Good Fit

8.D: Determining If a Line Is an Appropriate Model

 

Lesson 9: Bivariate Categorical Data

9.A: Categorical Data and Two-Way Tables

9.B: Comparative Bar Charts

9.C: Case Study

 

Lesson 10: Probability

10.A: Introduction to Probability

10.B: Study on Blood Pressure

10.C: Probability Rules

10.D: Conditional Probability and Independence

10.E: The Multiplication and Addition Rules

 

Lesson 11: Probability Distributions

11.A: Simulation

11.B: Probability Distributions of Discrete Random Variables

11.C: Probability Distributions of Continuous Random Variables

11.D: Constructing Probability Distributions

 

Lesson 12: The Normal Distribution

12.A: The Normal Distribution

12.B: z-Scores and Normal Distributions

12.C: Probability and Critical Values

12.D: Probability and Critical Values (continued)

 

Lesson 13: Sampling Variability

13.A: Sampling Variability

13.B: What Is a Sampling Distribution?

13.C: The Sampling Distribution of a Sample Proportion

13.D: Effect of Sample Size and the Value of the Population Proportion

13.E: The Standard Error

 

Lesson 14: Estimating a Population Proportion

14.A: Estimating a Population Proportion

14.B: Calculating a Margin of Error

14.C: Evaluating a Claim–Part 1

14.D: Evaluating a Claim–Part 2

 

Lesson 15: Confidence Intervals for a Population Proportion

15.A: Confidence Intervals and Confidence Levels

15.B.A: Confidence Interval for a Population Proportion

15.C: Interpreting Confidence Intervals and Margin of Error

 

Lesson 16: Hypothesis Testing About a Population Proportion

16.A: The Logic of Hypothesis Testing

16.B: Steps in Hypothesis Testing

16.C: Testing Hypotheses About a Population Proportion–Part 1

16.D: Testing Hypotheses About a Population Proportion–Part 2

 

Lesson 17: Sampling Distribution of a Sample Mean

17.A: Sampling Distribution of a Sample Mean

17.B: Effect of Sample Size and Variability in the Population

17.C: General Properties of the Sampling Distribution of a Sample Mean

 

Lesson 18: Inference About a Population Mean

18.A: t-Distributions

18.B: One Sample Confidence Interval for a Population Mean–Part 1

18.C: One Sample Confidence Interval for a Population Mean–Part 2

18.D: One Sample Hypothesis Test for a Population Mean–Part 1

18.E: One Sample Hypothesis Test for a Population Mean–Part 2

 

Lesson 19: Comparing Two Populations

19.A: Hypotheses About a Difference in Population Means or Proportions

19.B: Two-Sample Test for a Difference in Population Proportions

19.C: Paired Versus Independent Samples

19.D: Two-Sample Test for a Difference in Population Means Using Independent Samples

19.E: Inference for Paired Samples

19.F: Two-Sample Confidence Interval for a Difference in Population Proportions

19.G: Two-Sample Confidence Interval for a Difference in Population Means

 

Lesson 20: Analysis of Categorical Data: Chi-Square Goodness of Fit (Optional)

20.A: Quantifying the Strength of the Evidence

20.B: Conducting the Chi-Square Test

20.C: The Chi-Square Test and Degrees of Freedom

 

Lesson 21: Analysis of Categorical Data: Chi-Square Tests for Two-Way Tables (Optional)

21.A: Introduction to Chi-Square Tests for Two-Way Tables

21.B: Chi-Square Test for Independence

21.C: Chi-Square Test for Homogeneity

 

Lesson 22: Inference for Regression (Optional)

22.A: Sampling Distributions of Sample Slopes

22.B: Confidence Intervals for a Population Slope

22.C: Testing Claims About a Population Slope

 

Lesson 23: One-Way Analysis of Variance (Optional)

23.A: One-Way Analysis of Variance–Equal Sample Sizes

23.B: One-Way Analysis of Variance–Unequal Sample Sizes

23.C: Interpreting a One-Way Analysis of Variance

 

Answers (Odd)

Resources

  • 5-Number Summary and Boxplots
  • Categorical Data
  • The Chi-Square (χ2) Distribution
  • The Chi-Square (χ2) Goodness-of-Fit Test
  • The Chi-Square (χ2) Test for Homogeneity
  • The Chi-Square (χ2) Test for Independence
  • Confidence Intervals for Means
  • Confidence Intervals for Proportions
  • Experimental Studies
  • Fractions, Decimals, and Percentages
  • Hypothesis Testing for Means
  • Hypothesis Testing for Proportions
  • Inference for Regression
  • Introduction to Statistical Studies
  • Mean, Mode, and Median
  • The Normal Distribution
  • One-Way Analysis of Variance
  • Probability Rules
  • Sampling Methods
  • t-Distributions
  • Technology: Summary Statistics and LSR Line
  • Variance and Standard Deviation
  • Writing Principles
Glossary

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