Tested skills and knowledge |
Exercises |
|
Computing the mean, variance, and standard deviation of a dicrete probability distribution |
3.2, 3.3 |
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Binomial distribution: when to use; formulas for the probabilities, mean, variance, and standard deviation |
3.8, 3.15 |
| Continuous probability distributions: when to use; pdf and cdf | theoretical knowledge |
|
Normal distribution: the mean and variance; computing the probabilities associated with (possibly infinite) intervals using the table |
3.36--3.39 |
| The sample mean. Central Limit Theorem; when to use. | 3.42--3.45 |
| The sample variance. The t-distribution. | 3.50, 3.51, 3.53 |
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Confidence intervals for the unknown mean, in both cases: when the variance is known and when it is not. Calculation of the sample size. |
4.3, 4.4, 4.6 |
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Testing hypotheses for the unknown mean, in both cases: when the variance is known and when it is not. |
4.9(a,b), 4.10(a,b); 4.16 & 4.19 (except (c)) |
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Confidence intervals and testing hypotheses for the unknown variance. |
4.42, 4.43 |
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Simple linear regression: estimates of the parameters, including that of the variance; also, the determination coefficient. |
6.1, 6.2 |
| Experimental design: estimated effects and regression coefficients. | 7.2, 7.3(a), 7.8(a) |