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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
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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
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Performing Hypothesis Tests: Means
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Performing Hypothesis Tests: Proportions
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Performing Hypothesis Tests: Variance
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Critical Values and Rejection Regions
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Link Between Confidence Intervals and Hypothesis Testing
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Type I & Type II Errors
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10. Hypothesis Testing for Two Samples(0)

Two Proportions
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Two Means - Unknown, Unequal Variance
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Two Means - Unknown, Equal Variance
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Two Means - Known Variance
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Two Means - Matched Pairs (Dependent Samples)
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Two Variances and F Distribution
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11. Correlation(0)

Scatterplots & Intro to Correlation
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Correlation Coefficient
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12. Regression(0)

Linear Regression & Least Squares Method
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Residuals
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Coefficient of Determination
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Inferences for Slope
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Prediction Intervals
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Quadratic Regression
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13. Chi-Square Tests & Goodness of Fit(0)

Goodness of Fit Test
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Contingency Tables
(0)

Independence Tests
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Homogeneity Tests
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14. ANOVA(0)

Introduction to ANOVA
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Multiple Comparisons: Tukey Test
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Multiple Comparisons: Tukey-Kramer Test
(0)

Multiple Comparisons: Bonferoni Test
(0)

Two-Way ANOVA
(0)

1. Introduction to Statistics

Intro to Stats

1. Introduction to Statistics

Intro to Stats: Videos & Practice Problems

Video Lessons Practice Worksheet

Back to all problems

186 of 0

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Problem 186Multiple Choice

A survey was conducted among $1 comma 200$ residents of a city to determine their satisfaction with the public transportation services. The survey found that $68 percent sign$ of the respondents were satisfied with their services. Which part of this survey represents the descriptive branch of statistics? What conclusions might be drawn from the survey using inferential statistics?

The $68 percent sign$ satisfaction rate represents descriptive statistics, while inferential statistics might generalize that a similar proportion (around $68 percent sign$ ) of all city residents are satisfied with public transportation.

The $68 percent sign$ satisfaction rate represents inferential statistics, while descriptive statistics would list raw survey responses without summarization.

The $1 comma 200$ respondents represent descriptive statistics, while inferential statistics might conclude that exactly $68 percent sign$ of the city is satisfied.

The city’s total population represents descriptive statistics, while inferential statistics might conclude that satisfaction is unrelated to income level.

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