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Download Midterm II Content Summary Chptr. 5: Normal Distributions
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Midterm II Content Summary Chptr. 5: Normal Distributions - calculate and interpret z-scores find areas under standard normal curves probabilities for normally distributed variables find z-score given area from normal curve transform z-score to x-value find data value from a normal curve given a z-score apply the Central Limit Theorem to find the probability of a sample mean using a normal distribution to approximate the binomial distribution including the correction for continuity Chptr. 6: Confidence Intervals - calculate a point estimate and the margin of error construct and interpret confidence intervals for a population mean determine minimum sample size required when estimating µ construct confidence intervals for small sample sizes from normal populations with unknown standard deviations calculate a point estimate for a population proportion construct confidence intervals for a population proportion determine minimum sample size required when estimating a population proportion use the chi-square distribution to construct a confidence interval for a variance and standard deviation Chptr. 7: Hypothesis Testing - state a null and alternate hypothesis identify Type I and Type II errors distinguish between a one-tailed and two-tailed test interpret decision based on test find critical values for z-test use rejection regions for z-test find P-values and use to test a population mean find critical values in a t-distribution use t-test to test a population mean use z-test to test a population proportion find critical values for a chi-square test use chi-square test to test a variance or standard deviation Chptr. 8 + Chptr. 10.3: Two Sample and Variance Testing - decide whether two samples are independent or dependent conduct a two-sample z-test for the difference between two population means using large, independent samples conduct a t-test for the difference between two population means using small, independent samples conduct a t-test to test the mean of differences from a population of paired data conduct a z-test for differences between two population proportions calculate F-ratio, interpret F-distribution and critical F-values conduct two-sample F-test to compare two variances
