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Stat Exam 2
CH 5, 6, 7, & 8
| Question | Answer |
|---|---|
| Raw score | An original, untransformed observation or measurement. |
| Z-score | A standardized score with a sign that indicates direction from the mean (+ above µ and – below µ), and a numerical value equal to the distance from the mean measured in standard deviation. |
| Z-score transformation | A transformation that changes raw scores (X values) into z-scores. |
| Standard score | A score that has been transformed into a standard from. |
| Standardized distribution | An entire distribution that has been transformed to create predetermined values for µ and Theta |
| Z= | X-µ/ O |
| ZO = | X-µ = deviation score |
| X = | µ+ZO |
| Probability | Probability is defined as a proportion, a specific part out of the whole setoff possibilities. |
| Proportion | A part of the whole usually expressed as a fraction |
| Random sample | A sample obtained using a process that gives every individual an equal chance of being selected constant over a series of selections |
| Sampling with replacement | A sampling technique that returns the current selection to the population before the next selection is made. A required part of random sampling. |
| Independent events | Two events are independent if the occurrence of either one has no effect on the probability that the other will occur. |
| Normal distribution | A symmetrical, bell-shaped distribution with proportions corresponding to those listed in the unit normal table. |
| Unit normal table | A table listing proportions corresponding to each Z-score location in a normal distribution. |
| Percentile | A score that is identified by the percentage of the distribution that falls below a specific score. |
| Percentile rank | The percentage of a distribution that falls below a specific score. |
| Binomial distribution | the distribution of probabilities, for each possible outcome, for a series of observations of a dichotomous variable. |
| (A)p = | Number of ways event A can occur / Total number of possible outcomes |
| z= | X – pn / √npq |
| µ = | pn |
| O = | √npq |
| Distribution of sample means | The set of sample means from all the possible random samples for a specific sample size (n) from a specific population |
| Sampling distribution | a distribution of statistics (as opposed to a distribution of scores). The distribution of sample means is an example of a sampling distribution. |
| Expected value of M | The mean of the distribution of sample means. The average of the M values. |
| Standard error of M | The standard deviation of the distribution of sample means. The standard distance between a sample mean and the population mean. |
| The central limit theorem | A mathematical theorem that specifies the characteristics of the distribution of sample means. |
| Om= | O/√n or √((O^2)/n) |
| Z = | M-µ / Om |
| Hypothesis testing | A statistical procedure that uses data from a sample to test a hypothesis about a population |
| Null hypothesis, Ho | The null hypothesis states that there is no effect, no difference, or no relationship. |
| Alternative hypothesis, H1 | The alternative hypothesis states that there is an effect, there is a difference, or there is a relationship. |
| Type I error | A type I error is rejecting a true null hypothesis. You have concluded that a treatment does have an effect when actually it does not. |
| Type II error | A type II error is failing to reject a false null hypothesis. The test fails to detect a real treatment effect. |
| Alpha (a) | Alpha is a probability value that defines the very unlikely outcomes if the mull hypothesis is true. Alpha also is the probability of committing a Type I error. |
| Level of significance | The level of significance is the alpha level, which measures the probability of a Type I error. |
| Critical region | The critical region consists of outcomes that are very unlikely to be obtained if the null hypothesis is true. The term very unlikely is defined by (alpha) a. |
| Test statistic | A statistic that summarizes the sample data in a hypothesis test. The test statistic is used to determine whether or not the data are in the critical region. |
| Beta (ß) | Beta is the probability of a Type II error. |
| Directional (one-tailed) test | A directional test is a hypothesis test that includes a directional prediction in the statement of the hypotheses and place the critical region entirely in one tail of the distribution. |
| Effect size | A measure of the size of the treatment effect that is separate from the statistical significance of the effect. |
| Power | The probability that the hypothesis test will reject the mull hypothesis when there actually is a treatment effect |
| (Type I Error) p | a |
| Type II Error) p | ß |
| Cohen’s d | Mean difference / Standard Deviation = M -µ / O |
Created by:
ehlertbm
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