Psych 151 Exam 2

One-Tailed Hypothesis Test

Hypothesis that specifies either an increase or a decrease in the population mean, to make a statement about the direction of an effect

Sample Distribution

a distribution of the statistics obtained by selecting all of the possible samples of specific size from a population

Alpha Level

a probability value that is used to define the concept of very unlikely in a hypothesis test

Statistically Significant

a result that is very unlikely when the null hypothesis is true. The result is sufficient to reject the null hypothesis

Hypothesis Testing

a statistical method that uses sample data to evaluate a hypothesis about a population

Inferential Statistics

compare the sample after treatment with original population if treated sample is noticeably different from original population, can conclude treatment works

Critical Region

composed of the extreme sample values that are very unlikely to be obtained in the population by chance, determined by the alpha level

Type II Error

occurs when a researcher fails to acknowledge that the treatment was actually effectual and fails to reject the null hypothesis

Type I Error

occurs when a researcher rejects a null hypothesis that is actually true, saying that the treatment has an affect when it actually doesn't

Raw Scores

original, unchanged scores that are the direct result of a measurement

Alternative Hypothesis

predicts that the independent variable does have an effect on the dependent variable

Random Sampling

requires that each individual has an equal chance of being selected and that the probability of being selected stays constant from one selection to the next if more than one individual is being selected

Simple Random Sample

requires that each individual in the population has an equal chance of being selected

Z-Score

specifies the precise location of each x value within a distribution. The numerical value specifies the distance from the mean by counting the number of standard deviations between x and mu

Null Hypothesis

states that in the general population there is no change, difference, or relationship between the treatment and the scores

Law of Large Numbers

states that the larger the sample size, the more probable it is that the sample mean is close to the population mean

Distribution of Sample Means

the collection of sample means for all of the possible random samples of a particular size that can be obtained from the population

Central Tendancy

the mean of the distribution of sample means will always equal the population mean which is called the expected value of M

Expected Value of M

the mean of the distribution sample means is equal to the mean of the population scores

Sample Error

the natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter

Standard Error of M

the standard deviation of the distribution of sample means, provides a measure of how much distance is expected on average between a sample mean (M) and the population mean (mu)

Probability

used to predict what samples are likely to be obtained from a population