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17 Cards in this Set
- Front
- Back
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Central Limit Theorem |
sampling distributions of the mean will become more normal as: -N increases -if the population from which samples are drawn is normal |
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Empirical Vs Theoretical Distribution |
empirical is obtained via observation theoretical is by mathematical means-inferential statistics |
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Characteristics of a Good Estimator |
relatively efficient-sampling distribution has smaller standard error than another estimator consistent-gets closer to value of population parameter as sample size increases Sufficient-aspects of the sample data not involved in the definition of the estimator will not improve the estimator |
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Factors that affect Correlation size |
restricted range-when range is restricted, the correlation will decrease the correlaiton because sy'x becomes larger relative to the restricted sy selecting Extreme groups-increases r because it means selecting fewer subjects whose scores are near the means combined groups- samples often contain subgroups such as racial groups. when groups are combined the correlation may change and the r will not accurately refelct subgroups |
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Limitations of Hypothesis Testing |
asignificance depends on N-anything could be siginificant if N was large enough decision provides limited info-eg not how much of a relationship based on rejkect/do not reject h0-this creates a false dichotomous decision-it is not yes or no, it is more varied than that |
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Assumptions of Z Test |
1. Random Sampling 2. Normal Distribution (sampling distribution) 3. Interval or better 4. Asume H0 5. Independent Observations |
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Assumptions of Difference Between means test |
1. random sampling
2. normal sampling distribution 3. H0 assumed 4. Homogeneity of variance 5. interval or better data 6. independent observations |
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What is anova ratio |
between group variance/within group variance in other words error variance+systematic variance/error variance systematic variance is a result of manipulations of iv and dv-so if iv has no effect it will be zero and f will equal 1 |
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describe ratio for effect size in words |
variance in y associated with y's relationship to x/y's total variance |
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Measures of spread / variability |
sd, variance, range, interquartile range, |
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measures of central tendency |
mean, median, mode |
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what does histogram bar represent |
covers entire class interval |
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how do does one find the midpoint |
half of interval plus lower real limity |
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where is the point for frequency polygon |
midpoint |
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where is point for cumulative frequency polygon |
upper real limit |
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where is the pont in cumulative relative frequency polygon |
upper limit of class intervals |
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3 of mccalls 7 facts about sd and variance |
s and s^2 always positive as variance inscreases so does standard deviiton s ans S^2 will be zero if all scores in the distribtuion are the same |
