Describing Data | ||
11 Sep F | What is statistics, and can you lie with it? | Introduction |
14 Sep M | Displaying data distributions: Histograms | 1.0, 1.1, 1.2 , |
Averages | 1.3 up to p. 59 | |
16 Sep W | Measuring variability | 1.2 |
Percentiles | ||
Boxplots | ||
18 Sep F | Linear transformations | 1.3 |
Standardizing | ||
The Normal (Gaussian) distribution | ||
21 Sep M | Calculating normal probabilities | 1.3 |
Using Data Desk | ||
23 Sep W | Categorical and quantitative data | 2.0, 2.1, 2.2 |
Looking at bivariate relationships: scatterplots | ||
Positive and negative association | ||
Linear relationships | ||
Correlation: measuring linear association | ||
25 Sep F | Response and explanatory variables | 2.0, 2.3 |
Marginal and conditional distributions | ||
Smoothing: mean and median traces | ||
Regression as conditional mean | ||
Regression: least squares criterion | ||
Fitted values and residuals | ||
28 Sep M | The regression model | 2.3 |
Residual plots | ||
Transforming variables: taking logs | ||
Regression in Data Desk | ||
30 Sep W | Unusual values: outliers and influential points | 2.4, 157-159 |
Extrapolation | ||
Ecological correlations | ||
Aggregating data and Simpson’s paradox | ||
2 Oct F | Conditional distributions in regression | |
Regression effect | ||
5 Oct M | Predicting Y from X vs. predicting X from Y | |
Correlation and regression | ||
Displaying data visually | ||
Collecting Data | ||
7 Oct W | Correlation vs. causation | 2.4, 3.0, 3.2 |
Lurking variables | ||
Observational studies | ||
Design of experiments | ||
9 Oct F | Randomization | 3.2 |
Treatment and control groups | ||
Blocking and matched pairs | ||
12 Oct M | Practical issues in experiments | |
Ethics and experimentation | ||
AIDS placebo trials in developing nations | ||
14 Oct W | review | |
16 Oct F | Midterm 1 | |
21 Oct W | Ethics and experimentation | |
video: Milgram's experiment on obedience | ||
23 Oct F | Population vs. samples, parameters vs. statistics | 3.1 |
Representative sampling: quotas vs. random | ||
Simple random samples | ||
Other sampling designs | ||
26 Oct M | Biases in sampling | 3.1 |
28 Oct W | Overestimating rare events | |
False positives and false negatives | ||
Conditional probability | ||
Describing Sampling Variability | ||
30 Oct F | Sampling distributions | 4.0, 4.1 |
2 Nov M | Bias and variability | 4.1 |
Calculating probabilities | ||
4 Nov W | The sampling distribution of a proportion | 4.3 |
6 Nov F | Linear combinations of random variables | |
Expected value and variance of linear combinations | ||
9 Nov M | The sampling distribution of a sample mean | 4.5 |
Central Limit Theorem | ||
Drawing Inferences | ||
11 Nov W | Confidence intervals (s known) | 5.0, 5.1 |
13 Nov F | Interpreting confidence intervals | 5.1 |
16 Nov M | More on confidence intervals | |
review | ||
18 Nov W | Midterm 2 | |
20 Nov F | Hypothesis testing and p-values | 5.2 (omit 370-373) |
The one sample z-test | ||
23 Nov M | The t distribution | 6.0, 6.1 |
The one sample t-test | ||
25 Nov W | One sample t-test: Baby boom example | 6.1 |
30 Nov M | Confidence intervals (t-intervals) | 6.1 |
Confidence intervals and hypothesis tests | ||
2 Dec W | Type I and type II errors | 5.3, 5.4 up to p390 |
Interpreting hypothesis tests | ||
4 Nov F | Paired comparisons | 6.1 pp419-424 |
Comparing two means: two independent sample t-test | 6.2 up to p450 | |
7 Dec M | Comparing two means, cont. | 6.2 up to p450 |
Using Data Desk for projects | ||
9 Dec W | Comparing proportions | 7.0, 7.1, 7.2 |
11 Dec F | Projects | |
Final exam 17 Dec 9:30 |
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