# Math 120 Videos

### Course Videos

Each of these links send you to a play list of the videos for that chapter. The videos are listed both by section number and topic.

Chapter 1 — This chapter covers:

• Define Statistics and statistical thinking
• Explain the process of statistics
• Distinguish between qualitative and quantitative variables
• Distinguish between discrete and continuous variables
• Determine the level of measurement of a variable
• Distinguish between an observational study and an experiment
• Explain the various types of observational studies
• Obtain a simple random sample
• Obtain a stratified sample
• Obtain a systematic sample
• Obtain a cluster sample
• Explain the sources of bias in sampling
• Describe the characteristics of an experiment

Chapter 2 — This chapter covers:

• Organize qualitative data in tables
• Construct bar graphs
• Construct pie charts
• Organize discrete data in tables
• Construct histograms of discrete data
• Organize continuous data in tables
• Construct histograms of continuous data
• Draw stem-and-leaf plots
• Identify the shape of a distribution
• Construct frequency polygons
• Create cumulative frequency and relative frequency tables
• Construct frequency and relative frequency ogives
• Draw time-series graphs
• Describe what can make a graph misleading or deceptive

Chapter 3 — This chapter covers:

• Determine the arithmetic mean of a variable from raw data
• Determine the median of a variable from raw data
• Explain what it means for a statistic to be resistant
• Determine the mode of a variable from raw data
• Determine the range of a variable from raw data
• Determine the standard deviation of a variable from raw data
• Determine the variance of a variable from raw data
• Use the Empirical Rule to describe data that are bell shaped
• Use Chebyshev’s Inequality to describe any set of data
• Approximate the mean of a variable from grouped data
• Compute the weighted mean
• Approximate the standard deviation of a variable from grouped data
• Determine and interpret z-scores
• Interpret percentiles
• Determine and interpret quartiles
• Determine and interpret the interquartile range
• Check a set of data for outliers
• Compute the five-number summary
• Draw and interpret boxplots

Chapter 4 — This chapter covers:

• Draw and interpret scatter diagrams
• Describe the properties of the linear correlation coefficient
• Compute and interpret the linear correlation coefficient
• Determine whether a linear relation exists between two variables
• Explain the difference between correlation and causation
• Find the lest-squares regression line and use the line to make predictions
• Interpret the slope and the y-intercept of the least-squares regression line
• Compute the sum of squared residuals
• Compute and determine the coefficient of determination
• Perform residual analysis on a regression model
• Identify influential observations

Chapter 5 — This chapter covers:

• Apply the rules of probabilities
• Compute and interpret probabilities using the empirical method
• Compute and interpret probabilities using the classical method
• Recognize and interpret subjective probabilities
• Use the Addition Rule for disjoint events
• Use the General Addition Rule
• Compute the probability of an event using the Complement Rule
• Identify independent events
• Use the Multiplication Rule for independent events
• Compute at-least probabilities
• Compute conditional probabilities
• Compute probabilities using the General Multiplication Rule
• Solve counting problems using the Multiplication Rule
• Solve counting problems using permutations
• Solve counting problems using combinations
• Solve counting problems involving permutations with non-distinct items
• Compute probabilities involving permutations and combinations.
• Determine the appropriate probability rule to use
• Determine the appropriate counting technique to use

Chapter 6 — This chapter covers:

• Distinguish between discrete and continuous random variables
• Identify discrete probability distributions
• Construct probability histograms
• Compute and interpret the mean of a discrete random variable
• Interpret the mean of a discrete random variable as an expected value
• Compute the standard deviation of a discrete random variable
• Determine whether a probability experiment is a binomial experiment
• Compute probabilities of binomial experiments
• Compute the mean and standard deviation of a binomial random variable
• Construct binomial probability histograms

Chapter 7 — This chapter covers:

• Use the uniform probability distribution
• Graph a normal curve
• State the properties of the normal curve
• Explain the role of area in the normal density function
• Find and interpret the area under a normal curve
• Find the value of a normal random variable

Chapter 8 — This chapter covers:

• Describe the distribution of the sample mean:  normal population
• Describe the distribution of the sample mean:  non-normal population
• Describe the sampling distribution of a sample proportion
• Compute probabilities of a sample proportion

Chapter 9 — This chapter covers:

• Obtain a point estimate for the population proportion
• Construct and interpret a confidence interval for the population proportion
• Determine the sample size necessary for estimating a population proportion within a specified margin of error
• Obtain a point estimate for the population mean
• State properties of Student’s t-distribution
• Determine t-values
• Construct and interpret a confidence interval for a population mean
• Find the sample size needed to estimate the population mean within a given margin of error
• Find critical values for the chi-square distribution
• Construct and interpret confidence intervals for the population variance and standard deviation
• Determine the appropriate confidence interval to construct

Chapter 10 — This chapter covers:

• Determine the null and alternative hypotheses
• Explain Type I and Type II errors
• State conclusions to hypothesis tests
• Explain the logic of hypothesis testing
• Test hypotheses about a population proportion
• Test hypotheses about a population proportion using the binomial probability distribution
• Test hypotheses about a mean
• Understand the difference between statistical significance and practical significance
• Test hypotheses about a population standard deviation
• Determine the appropriate hypothesis test to perform

Chapter 11 — This chapter covers:

• Distinguish between independent and dependent sampling
• Test hypotheses regarding two proportions from independent samples
• Construct and interpret confidence intervals for the difference between two population proportions.
• Determine the sample size necessary for estimating the difference between two population Proportions
• Test hypotheses regarding matched-pairs data
• Construct and interpret confidence intervals about the population mean difference of matched-pairs data
• Test hypotheses regarding the difference of two independent means
• Construct and interpret confidence intervals regarding the difference of two independent means
• Find critical values of the F-distribution
• Test hypotheses regarding two population standard deviations
• Determine the appropriate hypothesis test to perform

Chapter 12 — This chapter covers:

• Perform a goodness-of-fit test
• Perform a test for independence
• Perform a test for homogeneity of proportions

Chapter 13 — This chapter covers:

• Verify the requirements to perform a one-way ANOVA
• Test a hypothesis regarding three or more means using one-way ANOVA

Chapter 14 — This chapter covers:

• State the requirements of the least-squares regression model
• Compute the standard error of the estimate
• Verify that the residuals are normally distributed
• Conduct inference on the slope
• Construct a confidence interval about the slope of the least-squares regression model
• Construct confidence intervals for a mean response

Chapter 15 — This chapter covers:

• Distinguish between parametric and nonparametric statistical procedures
• Inference about measures of central tendency