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Statistics

Statistics. Descriptive Statistics. Inferential Statistics. What You Need to Know for The Exam…. You will not have to conduct these tests in an exam(cue… sigh of relief) However you will have to; Know the purpose of using Inferential Statistics. Know what test you would use and why.

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Statistics

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  1. Statistics

  2. Descriptive Statistics

  3. Inferential Statistics

  4. What You Need to Know for The Exam…. • You will not have to conduct these tests in an exam(cue… sigh of relief) • However you will have to; Know the purpose of using Inferential Statistics. Know what test you would use and why. Whether or not the results are significant?

  5. Why are they used? 1)Statistical tests are used by Psychologists(and maths boffins) to prove or disprove a Hypothesis. 2) Statistical tests are used to determine whether data shows significance(if there is a relation or effect in the experiment). 3) Statistical tests see if the NULL Hypothesis is true(that results are due to chance/random). So the test is there to find out if the result was found by chance. 4) Which test you use depends on the data you have!

  6. Choosing the Correct Statistical Test To decide what test you will use you need the following information: Difference/Correlation/Association: (This you will gather from the information given in the statement provided to you on the test. Type of Participant Design: Independent Measures, Matched Pairs, Repeated Measures Type of Data: NOIR They may refer to the terms parametric and non parametric on your exam.

  7. Time for the Tough Bit! Spearman Observed value of Rho Wilcox Observed Value T Mann-Whitney Observed Value or U Chi ² Observed Value of x ² Sign Test Observed Value of S The Observed Value refers to the statistical calculation that you carry out (this will always be given to you on the exam). The Critical Value is found on the critical tables, which you may need to work out on the exam using the critical value tables.

  8. V. Whether or not the results are significant?

  9. A type 1 error is rejecting the null hypothesis when it should be accepted. A type 2 error is accepting the null hypothesis when it should be rejected. Errors

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