Videos to Accompany Sullivan Statistics

Chapter One - Data Collection

	Section 1.1: Introduction to the Practice of Statistics	Objectives
		1. Define statistics and statistical thinking
		2. Explain the process of statistics
		3. Distinguish between qualitative and quantitative variables
		4. Discrete versus continuous random variables

	Section 1.2: Observational Studies versus Designed Experiments	Objectives
		1a. Distinguish between an observational study and an experiment 1b. Distinguish between an observational study and an experiment
		2. Explain the various types of observational studies

	Section 1.3: Simple Random Sampling	Objective
		1. Obtain a Simple Random Sample by hand and Using MINITAB 1. Obtain a Simple Random Sample Using StatCrunch 1. Obtain a Simple Random Sample Using a TI84

	Section 1.4 Other Sampling Techniques	Objective
		Other Sampling Techniques

	Section 1.6: The Design of Experiments	Objective
		1. Describe the characteristics of an experiment
		2. Explain the steps in designing an experiment
		3. Explain the completely randomized design
		4. Explain the matched-pairs design

Chapter Two - Organizing and Summarizing Data

	Section 2.1: Organizing and Summarizing Data	Objectives
		1. Organize qualitative data in tables 2. Construct bar graphs Bar Graphs and Pie Charts in StatCrunch

	Section 2.2: Organizing Quantitative Data	Objectives
		1. Organize discrete data in tables 2. Construct histograms of discrete data 3 Organize continuous data in tables 4. Construct histograms of continuous data by hand and using TI84 4b. Histograms in StatCrunch 5. Draw stem-and-leaf plots 6. Draw dot plots 7. Identify the shape of a distribution

Chapter Three - Numerically Summarizing Data

	Section 3.1: Measures of Central Tendency	Objectives
		1. Determine the arithmetic mean of a variable from raw data by hand 1. Determine the mean of a variable from raw data using StatCrunch 2. Determine the median of a variable from raw data 2. Determine the median of a variable from raw data using StatCrunch 3. Explain what it means for a statistic to be resistant 4. Determine the mode of a variable from raw data

	Section 3.2: Measures of Dispersion	Objectives
		1. Compute the range of a variable from raw data 2. Compute the standard deviation of a variable from raw data 2a. Use StatCrunch to Find Measures of Central Tendency and Dispersion 4. Use the Empirical Rule to describe data that are bell shaped

	Section 3.3: Measures of Central Tendency and Dispersion from Grouped Data	1. Approximate the mean and standard deviation of a variable from grouped data using a TI84 1. Approximate the mean and standard deviation of a variable from grouped data using Excel

	Section 3.4: Measures of Position	Objectives
		1. Determine and interpret z-scores 2. Interpret percentiles 3. Determine and interpret quartiles 3. Determine and interpret quartiles using StatCrunch 4. Determine and interpret the interquartile range 5. Check a set of data for outliers

	Section 3.5: The Five Number Summary and Boxplots	Objectives
		1. Compute the five-number summary 2. Draw a boxplot by hand 2. Draw a boxplot using StatCrunch 2. Distribution shape from a boxplot

Chapter Nine - Estimating the Value of a Parameter Using Confidence Intervals

	Section 4.1: Scatter Diagrams and Correlation	Objectives
		1. Draw and interpret scatter diagrams 2. Understand the properties of the linear correlation coefficient 3. Compute and interpret the linear correlation coefficient 4. Determine whether a linear relation exists between two variables 5. Explain the difference between correlation and causation

	Section 4.2: Least Squares Regression	Objectives
		1. Find the least-squares regression line and use the line to make predictions 1. Find least-squares regression line using StatCrunch 2. Interpret the slope and the y-intercept of the least-squares regression line

	Section 4.3: Diagnostics on the Least Squares Regression Line	Objectives
		1. Compute and interpret the coefficient of determination 2. Perform residual analysis on a regression model 3. Identify influential observations

	Section 4.4: Contingency Tables and Association	Objectives
		1. Compute the marginal distribution of a variable 2. Use the conditional distribution to identify association among categorical data 3. Explain Simpson's Paradox

	Section 5.1: Probability Rules	Objectives
		1. Apply the rules of probabilities 2. Compute and interpret probabilities using the empirical method 3. Compute and interpret probabilities using the classical method 5. Recognize and interpret subjective probabilities

	Section 5.2: The Addition Rule and Complements	Objectives
		1. Use the Addition Rule for disjoint events 3. Compute the probability of an event using the Complement Rule

	Section 5.3: Independence and the Multiplication Rule	Objectives
		1. Identify independent events 2. Use the Multiplication Rule of independent events 3. Compute at-least probabilities

	Section 6.1: Discrete Random Variables	Objectives
		1. Distinguish between discrete and continuous random variables 2. Identify discrete probability distributions 3. Construct probability histograms 4. Compute and interpret the mean of a discrete random variable 5. Interpret the mean of a discrete random variable as an expected value Finding the mean and standard deviation of a discrete prob distn using Excel

	Section 6.2: The Binomial Probability Distribution	Objectives
		1. Determine whether a probability experiment is a binomial experiment 2. Compute probabilities of binomial experiments 2a. Computing binomial probabilities Using StatCrunch 3. Compute the mean and standard deviation of a binomial random variable 4. Construct binomial probability histograms Finding unusual results from a binomial experiment

	Section 7.1: Properties of the Normal Distribution	Objectives
		1. Utilize the uniform probability distribution 2. Graph a normal curve 3. State the properties of the normal curve 4. Explain the role of area in the normal density function

	Section 7.2: Applications of the Normal Distribution	Objectives
		1. Find and interpret the area under a normal curve by hand and MINITAB 1. Find and interpret the area under a normal curve by hand (using tables) 1. Find and interpret the area under a normal curve using StatCrunch 1. Finding area under normal curve using StatCrunch (another Example) 2. Find the value of a normal random variable by hand 2. Find the value of a normal random variable by hand (Part II) 2. Find the value of a normal random variable using StatCrunch 2. Find the value of a normal random variable using StatCrunch (another Example) Using z-sub alpha notation

	Section 7.3 Assessing Normality	1. Normal probability plots

	Section 8.1: Distribution of the Sample Mean	Objectives
		1a. Describe the distribution of the sample mean for samples obtained from a normal population 1b. Describe the distribution of the sample mean for samples obtained from a normal population 2a. Describe the distribution of the sample mean for samples obtained from a population that is not normal 2b. Describe the distribution of the sample mean for samples obtained from a population that is not normal

	Section 8.2: Distribution of the Sample Proportion	Objectives
		1a. Describe the sampling distribution of a sample proportion 1b. Describe the sampling distribution of a sample proportion 2a. Compute probabilities of a sample proportion 2b. Compute probabilities of a sample proportion

	Section 9.1: Confidence Intervals about a Population Proportion	Objectives
		1. Obtain a point estimate for the population proportion 2a. Construct and interpret a confidence interval for the population proportion - The Logic 2b. Construct and interpret a confidence interval for the population proportion by hand and using a TI-84 2c. Construct and interpret a confidence interval for the population proportion by hand 2d. How to obtain confidence interval for a proportion from StatCrunch 3. Determine the sample size necessary for estimating a population proportion within a specified margin of error

	Section 9.2: Confidence Intervals about a Population Mean	Objectives
		1. Know the properties of Student's t-distribution 3. Determine t-values 4a. Construct and interpret a confidence interval about a population mean 4b. Construct and interpret a confidence interval about a population mean by hand and using TI-84 4c. How to obtain a confidence interval for the population mean using StatCrunch 5. Find the sample size needed to estimate the population mean within a given margin of error

	Section 9.5: Bootstrapping	Objectives
		1. Estimate a parameter using the bootstrap method

	Section 10.1: The Language of Hypothesis Testing	Objectives
		1. Determine the null and alternative hypothesis 2. Understand Type I and Type II errors 3. State conclusions to hypothesis tests

	Section 10.2: Hypothesis Tests for a Population Proportion	Objectives
		1. Explain the Logic of Hypothesis Testing 2a. Test hypotheses about a population proportion - one-tailed test 2b. Test hypotheses about a population proportion - two tailed test 2c. Test hypotheses about a population proportion using StatCrunch

	Section 10.3: Hypothesis Tests for a Population Mean	Objective
		1a. Test hypotheses about a mean - large sample using P-value 1b. Test hypotheses about a mean - small sample using P-value 1c. Test hypotheses about a mean using technology 1d. Test hypotheses about a mean large sample using StatCrunch 1e. Test hypotheses about a mean small sample using StatCrunch 2. Understand the difference between statistical significance and practical significance

	Section 11.1: Inference about Two Proportions	Objectives
		1. Distinguish between independent and dependent sampling 2. Test hypotheses regarding two proportions from independent samples (TI-84) 2. Test hypotheses regarding two proportions from independent samples (StatCrunch) 3. Construct and interpret confidence intervals for the difference between two population proportions 4. Test hypotheses regarding two proportions from dependent samples

	Section 11.2 Inference about Two Means: Dependent Samples	Objectives
		1. Test hypotheses regarding matched-pairs data 2. Construct and interpret confidence intervals regarding matched-pairs data

	Section 11.3 Inferences about Two Means: Independent Samples	Objective
		1. Test hypotheses regarding the difference of two independent means 2. Construct and interpret confidence intervals for the difference between two independent means

	Section 12.1 Goodness-of-Fit Test	Objectives
		1a. Perform a goodness-of-fit test 1b. Perform a goodness-of-fit test 1c. Perform a goodness-of-fit test using StatCrunch (Adobe PDF)

	Section 12.2 Tests for Independence and the Homogeneity of Proportions	Objectives
		1a. Perform a test for independence 1b. Perform a test for independence 1c. Perform a test for independence using StatCrunch (Adobe PDF) 2a. Perform a test for homogeneity of proportions 2b. Perform a test for homogeneity of proportions using StatCrunch (Adobe PDF)

Section 14.1 Testing the Significance of the Least-Squares Regression Model	Objectives
	1. State the requirements of the least-squares regression model 2. Compute the standard error of the estimate (and a review of finding the regression model) 3. Verify that the residuals are normally distributed 4. Conduct inference on the slope 5. Construct a confidence interval about the slope of the least-squares regression model

Section 14.2 Confidence and Predication Intervals	Objectives
	1. Construct confidence intervals for a mean response (using StatCrunch) 2. Construct prediction intervals for an individual response (using StatCrunch)