introduction to psychological statistics

    Cards (23)

    • Statistics are used for purposes of description and we can also use it to make inferences.
    • Data analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data.
    • As researchers, we diagnose the problem, specify statistical tests, retrieve then interpret analysis results.
    • Psychological statistics is the application of formulas, theorems, numbers, and law to psychology.
    • Variable is a simple something that can vary and can be measured: that is, it can take on many different values or categories.
    • Independent Variable are what we expect will influence dependent variables.
    • Dependent Variable is what happens as a result of the independent variable.
    • Control Variable is anything that is held constant or limited in a research study. It's a variable that is not of interest to the study's aims but is controlled because it could influence the outcomes.
    • Psychological variables encompass a large range of factors relating to an individual's psychological state and social environment and potentially have either positive and negative consequences for health and behavioral outcomes.
    • Descriptive statistics simply gives a general picture of the scores in a given group and they include the measures of central tendency and the measures of variability.
    • Central tendency involves different kinds of averages: the mean, median, and mode. Variability involves the standard deviation, which indicates how far scores in a group are likely to be from the average.
    • Inferential Statistics uses to help psychologists draw inferences, or conclusions, from the data obtained from their research.

      Most common statistical test include the student's T-test and the analysis of variance (or F-test).
    • Population is the set of all individuals of interest in a particular study while sample is a set of individual selected from a population, usually intended to represent the population in a research study.
    • Parametric statistics refers to a branch of statistics that makes certain assumptions about the parameters of a population distribution from which the sample is drawn - powerful and provides presice estimates.
    • Normal Distribution is where the data is assumed to follow a probability distribution.
    • Homogeneity of Variance is the variance within each group being compared to be equal.
    • Independence is where the observations or samples are independent of each other.
    • Non-parametric statistics refers to a branch of statistics that does not make strong assumptions about the underlying population distribution.
    • Level of measurement is a kind of scale used to measure a response.
    • Nominal is the simplest level of measurement and involves categorizing data into distinct categories or groups without any specific order or hierarchy.
    • Ordinal is the value of the numerical scores tell us which is the smallest, the next smallest, and so forth up to largest - there is a rank or ordering of responses.
    • Interval measures magnitude or quantitative sie using measures with equal intervals between the values - it has no true zero point.
    • Ratio is the exactly the same as interval scale measure with one important priviso - absolute zero that is meaningful/has true zero.
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