A small startup surveys 44 employees about their favorite morning drink and records: coffee, coffee, tea, tea. Coding 'coffee' as 11 and 'tea' as 00 produces the data {1,1,0,0}\left\lbrace1,1,0,0\right\rbrace. Ten bootstrap samples (resampling with the replacement, each of size 44) yield these sorted bootstrap proportions (of 11’s): 0.00,0.25,0.25,0.50,0.50,0.50,0.75,0.75,0.75,1.000.00,0.25,0.25,0.50,0.50,0.50,0.75,0.75,0.75,1.00. Using only these ten values, construct an 80%80\% confidence interval estimate of the true proportion of employees whose favorite drink is coffee.

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1. Intro to Stats and Collecting Data(0)

Intro to Stats
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Levels of Measurement
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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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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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Basic Concepts of Probability
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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 and 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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Goodness of Fit Test
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Multiple Comparisons: Bonferoni Test
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Two-Way ANOVA
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8. Sampling Distributions & Confidence Intervals: Proportion

Confidence Intervals for Population Proportion

8. Sampling Distributions & Confidence Intervals: Proportion

Confidence Intervals for Population Proportion: Videos & Practice Problems

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Problem 52Multiple Choice

A small startup surveys $4$ employees about their favorite morning drink and records: coffee, coffee, tea, tea. Coding 'coffee' as $1$ and 'tea' as $0$ produces the data $the set 1 comma 1 comma 0 comma 0$ . Ten bootstrap samples (resampling with the replacement, each of size $4$ ) yield these sorted bootstrap proportions (of $1$ ’s): $0.00 comma 0.25 comma 0.25 comma 0.50 comma 0.50 comma 0.50 comma 0.75 comma 0.75 comma 0.75 comma 1.00$ . Using only these ten values, construct an $80 percent sign$ confidence interval estimate of the true proportion of employees whose favorite drink is coffee.

$25 percent sign is less than p is less than 100 percent sign$

$25 percent sign is less than p is less than 75 percent sign$

$50 percent sign is less than p is less than 75 percent sign$

$75 percent sign is less than p is less than 100 percent sign$

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