POLS 3650 Lecture Notes - Lecture 10: Collectively Exhaustive Events, Null Hypothesis, Kurtosis
13 Feb 2017
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Overview: standardizing a normal distribution, statistical inference, what was the central limit theorem again, confidence intervals for means, confidence intervals for proportions, the t-distribution. Let"s say the weight of cats is normally distributed with a mean of 10 pounds and a standard deviation of 1. 5 pounds: mr. whiskers weighs 13 pounds. What z-score is associated with this weight: z score = +2, what percentage of cats weight more than mr. whiskers, 2. 3, only 16 percent of cats is lighter than ginger. What z-score is associated with this percentage: z score = -1, how much does ginger weigh, 8. 5 lbs. Statistical inference: statistical inference is the process of making claims about parameter values on the basis of point estimates. Sampling distribution: x-axis raw values, y-axis number of cases, standard deviation called standard deviation, can have any shape (skewed, multimodal, ) Is produced in any univariate analysis: x-axis point estimates, y-axis number of samples, standard deviation called standard error.
