PSYC209 Vocab Exam 2

sampling distribution

a distribution of all sample means that could be obtained in samples of a given size from the same population

sample design

a specific plan or protocol for how individuals will be selected or sampled from a population of interest

significance level

a criterion of judgement upon which a decision is made regarding the value stated in a null hypothesis, criterion based on probability of obtaining a statistic measured in the sample if the value stated in the null hypothesis were true, typically set at 5%

z statistic

an inferential statistic is used to determine the number of standard deviations in a standard normal distribution that a sample mean deviates from the population mean stated in the null

unbiased estimator

any sample statistic obtained from a randomly selected sample that equals the value of its respective population parameter on average

critical value

cutoff value that defines the boundaries beyond which less than 5% of the sample means can be obtained if the null hypothesis is true, sample means obtained beyond a critical value will result in a decision to reject the null hypothesis

hypothesis

statement or proposed explanation for an observation, phenomenon or scientific problem that can be tested using the research method, often a statement about the value for a parameter in a population

statistical significance

describes a decision made concerning a value stated in the null hypothesis, when the null is rejected we reach significance, when the null is retained we fail to reach significance

effect

difference between a sample mean and the population mean stated in the null hypothesis, an effect is not significant when we retain the null hypothesis but is significant when we reject it

one-tailed/directional test

hypothesis tests in which the alternative hypothesis is stated as greater that or less than a value stated in the null hypothesis, the researcher is interested in a specific alternative to the null hypothesis

two-tailed/nondirectional test

hypothesis tests in which the alternative hypothesis is stated as not equal to a value stated in the null hypothesis, researcher is interested in any alternative to the null hypothesis

power

in hypothesis testing, the probability of rejecting a false null hypothesis

increase power by...

increasing: effect size (d), sample size (n) (reduces standard error, increases value of test statistic in hypothesis testing), alpha decreasing: beta (type II error), population standard deviation (sigma), standard error (s sub M)

test statistic

mathematical formula that identifies how far or how many standard deviations a sample outcome is from the value stated in a null hypothesis, allows researchers to determine the likelihood of obtaining sample outcomes if the null hypothesis were true, its value is used to make a decision regarding a null hypothesis

Cohen's d

measure of effect size in terms of the number of standard deviations that mean scores shifted above or below the population mean stated by the null hypothesis, the larger the value of d the larger the effect in the population, increase in d --> increase in power

hypothesis/significance testing

method for testing a claim or hypothesis about a parameter in a population using data measured in a sample, test a hypothesis by determining the likelihood that a sample statistic would be selected if the hypothesis regarding the population parameter were true

sampling without replacement

method of sampling in which each participant or item selected is not replaced before the next selection, most common method of sampling used in behavioral research, probabilities each selection are not the same

sampling with replacement

method of sampling in which each participant or item selected is replaced before the next selection, replacing before the next selection ensures that the probability for each selection is the same, this method of sampling is used in the development of statistical theory

p value

probability of obtaining a sample outcome, given that the value stated in the null hypothesis is true

central limit theorem

regardless of the shape of the population, the shape of the sampling distribution of the mean approximates a normal curve if the sample size is sufficiently large, It is NOT about the number of samples, but the size of the sample.

null hypothesis

statement about a population parameter, such as the population mean, that is assumed to be true, it is a starting point

alternative hypothesis

statement that directly contradicts the null hypothesis by stating that the actual value of a population parameter is less than, greater than, or not equal to the value stated in the null hypothesis

effect size

statistical measure of the size of an effect in a population which allows researchers to describe how far scores shifted in the population or the percent of variance that can be explained by a given variable

one-sample z test

statistical procedure used to test hypotheses concerning the mean in a single population with a known variance

sampling error

the extent to which sample means selected from the same population differ from one another, this difference, which occurs by chance, is measured by the standard error of the mean

alpha level

the level of significance or criterion for a hypothesis test, largest probability allowed

Type I error (alpha)

the probability of rejecting a null hypothesis that is actually true, researchers directly control the probability for committing one of these errors

Type II error (beta)

the probability of retaining a null hypothesis that is actually false

rejection region

the region beyond a critical value in a hypothesis test, we decide to reject the null hypothesis when the when the value of a test statistic is in this region

standard error (of the mean)

the standard deviation of a sampling distribution of sample means, the distance that sample mean values deviate from the value of the population mean

obtained value

the value of a test statistic, this value is compared to the critical value(s) of a hypothesis test to make a decision, when the obtained value exceeds a critical value, we decide to reject the null hypothesis; otherwise we retain the null hypothesis

type III error

type of error possible with one-tailed tests in which a decision would have been to reject the null hypothesis, but the researched decides to retain the null hypothesis because the rejection region was located in the wrong tail (wrong tail means the opposite tail from where a difference was observed and would have otherwise been significant)