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