Understanding the Basis of Statistical Power in Psychology Research Work What is Statistical Power? The power of a statistical test for a null hypothesis is the probability of having the basis to correctly reject a false null hypothesis (Greene, 2000). Statistical power is the probability of detecting an effect if the effect actually exists or the probability that the test will lead to a conclusion that the effect actually exists (High, 2000 & Cohen, 1988, p. 4). It is also the ability of the test to report a statistically significant effect where an actual effect of a given magnitude exists. In simple terms, statistical power is the likelihood that a researcher will discover an effect of a certain size in a statistical test no matter how small.
False The F test assumes that the sampled populations are not normal. A. True B. False The F test for equality of two variances tests whether the ratio of the sample variances differ significantly from 1. A.
Particularly, using the Spearman-Brown convention to find internal consistency in diversified test details. One such test is Inter-item consistency. Internal consistency pertains to the makeup of a test; It is the method of measuring dependability. It attests the degree in which items of a test measure only several facets of the same integer. With increase in the number of test the reliability of a test increases.
The following shall describe these two tests as well as explore their validity and reliability. Firstly, objective tests ensure restricted responses, such as true or false questionnaires or multiple-choice). Objective tests are usually standardized and based on the big five. They are commonly self reports and therefore explore conscious thought. A widely used example is the MMPI.
4. The data in the scatter plot can be modeled using a function of the form T= a x b^t +c Find values of a, b, and c that produce a reasonable model. A=.048332 B= -3.8573 C=
Unit 11 Intelligence test- a method for assessing an individual’s mental aptitudes and comparing them with those others, using numerical scores Intelligence- mental quality consisting of the ability to learn from experience, solve problems, and use knowledge to adapt to new situations Spearman’s General intelligence (g)- a general intelligence factor that, according to Spearman and others, underlies specific mental abilities and is therefore measured by every task on an intelligence test ex. Good at one good at all Factor analysis- a statistical procedure that identifies clusters of related items called factors on a test; used to identify different dimensions of performance that underlie a person’s total score ex. same topics on a test Savant syndrome- a condition in which a person otherwise limited in mental ability has an exceptional specific skill, such as in computation or drawing (math or art or music) ex. eric GARDENER’S EIGHT INTELLIGENCES Aptitude Exemplar 1. Linguistic T.S.
1. The researchers analyzed the data they collected as though it were at what level of measurement? a. Nominal b. Ordinal c. Interval/ratio d. Experimental 2. What was the mean posttest empowerment score for the control group? The mean/average posttest empowerment score for the control group was 97.12.
Selected Answer: Expected Value of Perfect Information Question 12 In the Monte Carlo process, values for a random variable are generated by __________ a probability distribution. Selected Answer: Sampling from Question 13 Consider the following frequency of demand: If the simulation begins with 0.8102, the
RES342 Week 3 Quiz 1. A frequency distribution can be shown as • a statistic • a histogram • a scatter plot • a stem and leaf plot 2. Simple statistics are • for simpletons • presented in stem and leaf plots • things like correlations • things like standard deviations 3. What would you do with a median? • Use it do show spread.
What are the independent and dependent variables in Figures 3, A, B, and C? How would you describe the relationship between the variables in Figures 3, A, B, and C? 3. Was there a signifi cant difference in the y intercept for the lines of best fi t in Figure 2 from the y intercept for the lines of best fi t in Figure 3? Provide a rationale for your answer.