strengths of various long-term memories. Memory improves when there is an increase in. depth of processing. the main contribution of the levels-of-processing principle is that it accounts for. the varying strengths of long-term memories.
In the traditional information-processing model, one difference between short-term memory and long-term memory is that... you forget many short-term memories almost as soon as your attention is distracted; long term memories can be available at any time.
Psychologists use the term memory to refer to. the process of retaining information as well as to the information retained. When comparing human memory to a computer, most psychologists today would agree... human memory is really not similar to computers.
procedural memory. You are asked to sketch a picture of your general psychology lecture hall. While you never actually tried to remember the types of chairs and the color of the carpet, you are told that your drawings has a # of correct features. Your memory for your classroom would be an example of... implicit memory.
can detect weaker memories than the recall method. People who seem to have forgotten some information may be able to remember that same information if you... change the method of testing. After you witness a robbery, you have trouble describing the thief.
Parametric tests usually have stricter requirements than nonparametric tests, and are able to make stronger inferences from the data. They can only be conducted with data that adheres to the common assumptions of statistical tests.
T-tests are used when comparing the means of precisely two groups (e.g. the average heights of men and women).
If the value of the test statistic is less extreme than the one calculated from the null hypothesis, then you can infer no statistically significant relationship between the predictor and outcome variables.
They can be used to: determine whether a predictor variable has a statistically significant relationship with an outcome variable. estimate the difference between two or more groups. Statistical tests assume a null hypothesis of no relationship or no difference between groups.
If your data do not meet the assumptions of normality or homogeneity of variance, you may be able to perform a nonparametric statistical test, which allows you to make comparisons without any assumptions about the data distribution.
Non-parametric tests don’t make as many assumptions about the data , and are useful when one or more of the common statistical assumptions are violated. However, the inferences they make aren’t as strong as with parametric tests.
To determine which statistical test to use, you need to know: whether your data meets certain assumptions. the types of variables that you’re dealing with.