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# Goals

Topics: Descriptive Statistics. Math Review.
You should be able to:
• Evaluate arithmetic expressions using the correct order of evaluation
• Evaluate mathematical formulas which involve the summation sign
• Substitute numbers into formulas and correctly evaluate the resulting
• Explain intuitively the concept of a measure of central tendency
• Define and calculate the median of a collection of numeric data
• Define and calculate the arithmetic mean of a collection of numeric data expressions

# Goals

Topics: Descriptive Statistics. Math review.
You should be able to:
• Explain why both the mean and median are measures of central tendency, and compare and contrast their usefulness
• Explain intuitively the concept of a measure of spread
• Define and calculate the sample variance and sample standard deviation of a collection of numeric data
• Explain why the sample variance is a measure of spread
• Define and calculate the interquartile range of a collection of data
• Define nominal, ordinal, discrete, and continuous data
• Define relative frequency, and give examples of its use
• Understand the relation between the sample mean and the relative frequency
• Explain intuitively the concept of a sampling distribution
• Construct a histogram from a collection of numeric data
• Understand what it means for a distribution to be skewed
• Construct and read simple x-y plots
• Understand a two-by-two cross-classification table

# September 12, 2001

Topics: Probability theory. Sample spaces. Independence.
You should be able to:
• Understand that probability is defined in terms of limiting relative frequencies
• Understand that probabilities are numbers between zero and one
• Understand the concept of a sample space
• Understand how to compute the probability of the complement of an event, given the probability of the event
• Be able to calculate simple probabilities involving equally likely events (such as rolls of a fair die, etc.)
• Understand the concept of mutually exclusive events
• Understand the addition rule of probability
• Understand the concept of independence
• Understand the multiplication rule for independent events
Proceed to probability theory notes.

# September 19, 2001

Topics: Probability theory. Independence and conditional probability.
You should be able to:
• Understand the definition of conditional probability.
• Understand the law of total probability
• Understand Bayes' Rule
• Understand various public health applications of probability theory
• Understand sensitivity, specificity, and the predictive value of a positive.

# September 26, 2001

Topics: Probability theory. Binomial distribution. Expectation. Population variance. Cumulative distribution function.
You should be able to:
• Understand how to compute the number of permutations of K distinguishable objects.
• Understand how to compute the number of ways to choose K objects out of N distinguishable objects.
• Understand the binomial distribution.
• Understand the definition of expectation.
• Understand the relation between expectation and sample mean.
• Understand that the expectation of the binomial distribution is Np, where N is the number of trials and p is the success probability per trial.
• Understand how the binomial is a model of sampling from a large population, or of sampling with replacement.
• Understand the concept of population variance.
• Understand the concept of cumulative distribution function.

# October 3, 2001

Topics: Statistical inference. Estimating a population proportion using the relative frequency. Hypothesis testing in general. Fisher's Exact Test. The Chi-square Test of Homogeneity in a R by C table. The Chi-square test of independence.

# October 10, 2001

Topics: Statistical inference. The sample variance again. The standard error of a sample mean. The normal distribution. The Z-test to compare a sample mean to a putative pre-selected population mean. The Z-test for a single proportion.

# October 17, 2001

Topics: Statistical inference. The one-sample T-test to compare a sample mean to a constant. The paired-sample T-test.

# October 24, 2001

Topics: Statistical inference. Pooled variance estimators. The two-sample T-test. One-way analysis of variance (beginning).

# October 31, 2001

Topics: Statistical inference. One-way analysis of variance. The within-mean-square. The between-mean-square. The F-test.

# November 7, 2001

Topics: Statistical inference. Linear regression. The regression mean square. The residual mean square. The T-test for the regression coefficient. The F-test of regression.

# November 14, 2001

Topics: Statistical inference. Correlation. Testing whether the correlation coefficient is zero. Relation to linear regression. The squared multiple correlation coefficient.
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