Spring 2005

# Midterm Exam 2, Friday, Mar. 18

The exam will be worth 100 points (out of 500 for the whole course). Students are responsible for all material covered in lectures since the first midterm and all material in Chapters 10, 11, 12, 13, 16, 17, and 18 of the textbook.

There are some practice problems available, along with answers. Please remember that on the actual exam, a calculator will not be necessary. However, you may use one if you wish. (Some of the sample exam questions would benefit from the use of a calculator, but on the actual exam these questions will have answers listed in a way such that a calculator is unnecessary.)

The following brief outline of topics from the book is not an exhaustive list of things you need to know, but it may help you make sure you have covered the main ideas.

## Chapter 10

Descriptive methods for two measurement variables

Interpretation, properties, and features of correlation

Interpretation of statistical significance

Masking or grouping of variables; its effect on the slope and intercept of regression lines

Interpretation of the slope and intercept

Using the regression equation for prediction

Link between sign of the slope and sign of the correlation coefficient

Statistical relationship vs. deterministic relationship

Regression: designation of the response (outcome) variable and the explanatory (independent or predictor) variable

Statistical significance, practical significance

Effect of sample size on statistical significance and practical significance

"Two warnings" on pp. 182-183 of the textbook

Issue of extrapolation - when to avoid

## Chapter 11

Impact of outliers on correlations

Legitimate outliers, illegitimate correlation

Correlation does not cause imply causation

Limitation of "cause and effect" statements with statistically significant correlations

## Chapters 12 and 13

Assessing statistical significance with the chi-squared statistic and the corresponding p-value:
1. Calculation of expected numbers in a 2x2 contingency table
2. Comparing expected and observed numbers
3. Calculating the chi-squared statistic
4. Determination of statistical significance using the chi-squared statistic
5. General properties of the chi-squared statistic

Interpreting a two-dimensional bar graph to determine any relationship between two variables

Calculation and interpretation of risk, relative risk, increased risk, and odds

Interpretation of 2x2 tables and tables which are not 2x2 using row percentages or two-dimensional bar graphs

Inference for statistically significant relationship between two variables

Link between relative risk and the chi-squared statistic

Similarities and differences between correlation and the chi-squared statistic

Identification of the response and explanatory variable

## Chapter 16

Interpretation of personal probability (Section 16.3)

The relative-frequency interpretation of probability (Section 16.2)

Determining the probability of an outcome under the relative-frequency interpretation

Interpretation: Two different methods (page 299)

Idea and interpretation of long-run relative frequency

Summary of relative-frequency interpretation of probability (Page 300 textbook)

Application of "Four Simple Probability Rules" (Pages 302 - 304)

Mutually exclusive events

Independent events

When will it happen? The number of attempts needed to achieve success

Accurate prediction of long-term outcomes

Calculation and interpretation of expected value (EV)

Expected value as a mean

## Chapter 17

Difference between population and sample

The certainty effect; the attractiveness of reducing risk to zero

The pseudocertainty effect

Distortion of personal probabilities

The availability heuristic

Anchoring

The representativeness heuristic

The conjunction fallacy: Believing Pr(A and B) is greater than Pr(A)

Forgotten base rates

The dangers of extreme optimism, conservativeness, or overconfidence

Calibrating the personal probabilities of experts

Ues of relative frequency to assess accuracy of personal probabilities

Seven suggestions for improving personal probabilities

## Chapter 18

Coincidences, and how often they happen to someone, somewhere, someday

Calculation of birthday probabilities

The Birthday Problem and its relationship to coincidences that seem improbable

General definition of a coincidence

The gambler's fallacy and its link to streaks, sequences, and coincidences

The law of small numbers

Memoryless nature of independent events

Small samples cannot be expected to accurately represent a population

Confusion of the inverse, and which two probabilities are typically reversed

Definition of false positive and false negative

Definition of sensitivity, specificity

Calculation of sensitivity, specificity

Calculation of the probabilities of a false positive or a false negative

Determining the actual probability (Bayes' Rule)

Accuracy of medical tests (base rate size and specificity/sensitivity values resulting in small probability of false positives)

Using expected values for decision-making