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1. Introduction to Statistics(0)

Intro to Stats
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Intro to Collecting Data
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Sampling Methods
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2. Describing Data with Tables and Graphs(0)

Visualizing Qualitative vs. Quantitative Data
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Frequency Distributions
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Histograms
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Bar Graphs and Pareto Charts
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Pie Charts
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Frequency Polygons
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Dot Plots
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Stemplots (Stem-and-Leaf Plots)
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Time-Series Graph
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3. Describing Data Numerically(0)

Mean
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Median
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Mode
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Standard Deviation
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Interpreting Standard Deviation
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Percentiles & Quartiles
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Boxplots
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4. Probability(0)

Basic Concepts of Probability
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Complements
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Addition Rule
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Multiplication Rule: Independent Events
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Introduction to Contingency Tables
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Multiplication Rule: Dependent Events
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Bayes' Theorem
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Fundamental Counting Principle
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Counting
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5. Binomial Distribution & Discrete Random Variables(0)

Discrete Random Variables
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Binomial Distribution
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Poisson Distribution
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Hypergeometric Distribution
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6. Normal Distribution & Continuous Random Variables(0)

Uniform Distribution
(0)

Standard Normal Distribution
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Non-Standard Normal Distribution
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7. Sampling Distributions & Confidence Intervals: Mean(0)

Sampling Distribution of the Sample Mean and Central Limit Theorem
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Introduction to Confidence Intervals
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Confidence Intervals for Population Mean
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Determining the Minimum Sample Size Required
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8. Sampling Distributions & Confidence Intervals: Proportion(0)

Sampling Distribution of Sample Proportion
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Confidence Intervals for Population Proportion
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Chi Square Distribution
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Confidence Intervals for Population Variance
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9. Hypothesis Testing for One Sample(0)

Steps in Hypothesis Testing
(0)

Performing Hypothesis Tests: Means
(0)

Performing Hypothesis Tests: Proportions
(0)

Performing Hypothesis Tests: Variance
(0)

Critical Values and Rejection Regions
(0)

Link Between Confidence Intervals and Hypothesis Testing
(0)

Type I & Type II Errors
(0)

10. Hypothesis Testing for Two Samples(0)

Two Proportions
(0)

Two Means - Unknown, Unequal Variance
(0)

Two Means - Unknown, Equal Variance
(0)

Two Means - Known Variance
(0)

Two Means - Matched Pairs (Dependent Samples)
(0)

Two Variances and F Distribution
(0)

11. Correlation(0)

Scatterplots & Intro to Correlation
(0)

Correlation Coefficient
(0)

12. Regression(0)

Linear Regression & Least Squares Method
(0)

Residuals
(0)

Coefficient of Determination
(0)

Inferences for Slope
(0)

Prediction Intervals
(0)

Quadratic Regression
(0)

13. Chi-Square Tests & Goodness of Fit(0)

Goodness of Fit Test
(0)

Contingency Tables
(0)

Independence Tests
(0)

Homogeneity Tests
(0)

14. ANOVA(0)

Introduction to ANOVA
(0)

Multiple Comparisons: Tukey Test
(0)

Multiple Comparisons: Tukey-Kramer Test
(0)

Multiple Comparisons: Bonferoni Test
(0)

Two-Way ANOVA
(0)

8. Sampling Distributions & Confidence Intervals: Proportion

Sampling Distribution of Sample Proportion

8. Sampling Distributions & Confidence Intervals: Proportion

Sampling Distribution of Sample Proportion: Videos & Practice Problems

Video Lessons Practice Worksheet

Back to all problems

42 of 0

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Problem 42Multiple Choice

A national health survey reports that $65 percent sign$ of adults aged $25$ to $40$ eat breakfast every day. You randomly select a sample of $220$ adults in this age group and find that only $120$ of them report eating breakfast daily. After performing a one-sample proportion z-test, you calculate a $z$ -score of $en dash 5.03$ . Based on the z-score, can you conclude that this sample is representative of the population at the $alpha equals 0.05$ level?

Yes, the $z$ -score falls within the acceptance region, so the sample is representative.

No, the $z$ -score is too small to support the claim, but it is not statistically significant.

No, the $z$ -score falls in the rejection region, so the sample is not representative.

Yes, although the $z$ -score is negative, it still supports the population claim.

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