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t Statistics, Correlation, and Regression - Coggle Diagram
t Statistics, Correlation, and Regression
The values in the sample must consist of independent observations.
The population sampled must be normal.
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The number of scores in the sample and the magnitude of the sample variance both have a large effect on the t statistic.
notice what happens to the width of the interval when you change the level of confidence.
note what happens to the width of the interval if you change the sample size.
The bigger the sample, the smaller the interval.
Confidence interval: is a range of values centered around a sample statistic. Can confidently estimate that the value of the parameter should be located in the interval near to the statistic.
The sign (+ or -) of the Pearson’s correlation tells us the direction of the relation between the variables, the form of the relationship, and the strength/consistency of the relationship between variables.
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A positive relationship means that X and Y vary in the same direction. A negative relationship means that X and Y vary in opposite directions.
A correlation of 1.00 indicates a perfect relationship, demonstrating a linear line. 0 displays there is no relationship at all and will show no linear trend.
Scatterplots: diagram of relationship between two variables. X scores represented along horizontal axis and Y scores represented along vertical axis.
A correlation between two variables should not be interpreted as implying a causal relationship. Simply because X and Y are related does not mean that X causes Y or that Y causes X.
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Correlations used for: prediction, validity, and reliability.
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