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PSYCHOLOGY COURSEWORK THE RESULTS RATIONALE/PURPOSE • The results section is where you report the results that you have found from your experiment. • You must report exactly what you found, however you must not explain why you found it here, this goes in the discussion. ASSESSMENT CRITERIA HL Criterion E - 2 marks Results are clearly stated and accurate and reflect the hypotheses and research. Appropriate descriptive statistics are applied to the data and their use is explained. The graph of results is accurate, clear and directly relevant to the study. Results are presented in both words and tabular form. HL Criterion F – 3 marks An appropriate inferential statistics test has been chosen and explicitly justified. Results of the inferential statistical test are accurately stated. The null hypothesis has been accepted or rejected appropriately according to the results of the statistical test. A statement of statistical significance is appropriate and clear. THE ESSENTIALS • • • • • The essential elements of your results section are as follows: Descriptive statistics (justification of and explanation of) The results table (of descriptive statistics) Graph (of descriptive statistics) Inferential statistics (justification of and interpretation of) DESCRIPTIVE STATISTICS • Your project must contain two forms of descriptive statistics 1) measures of central tendency - (i.e. mean/ median/ mode) • 2) measure of dispersion - (i.e. standard deviation) • MEASURES OF CENTRAL TENDENCY This includes the mean, median and mode. You must first of all justify why you have chosen to use the mean, median or mode, i.e. what are the strengths and weaknesses of them? Which is the most appropriate? Why? MEASURES OF CENTRAL TENDENCY Then, you must include a table of the calculated values of mean, median or mode. Do NOT include your workings out here, they go in the appendix (see ‘additional important resources’). You can use a calculator. MEASURES OF CENTRAL TENDENCY Then, you must explain what the calculated values show. This must be detailed, i.e. Are the values larger for condition A or B? Are the m/m/m values the same in condition A and the same in condition B? Why/not? Are there any obvious outliers in the results table which may have distorted the mean? Etc. MEASURE OF DISPERSION The appropriate measure of dispersion for interval/ratio data is the standard deviation. This shows how spread out the data are from the mean. You must first justify why you have chosen this. Hint! Look in the Course Companion p398 for the conditions under which the SD is used. MEASURE OF DISPERSION Then, you must include the calculated value of the standard deviation for conditions A and B in a table. Do NOT include your workings out here, they go in the appendix (see ‘additional important resources’) You can use a calculator. MEASURE OF DISPERSION Then, you must explain what the calculated value shows. This must be detailed, i.e. Which SD is larger? What does this mean? THE RESULTS TABLE • • • • You must include a table of results. Not raw data, this goes in the appendices. To do this, it is easier if you label your conditions with an identifiable label, whilst also naming your conditions ‘A’ and ‘B’. Condition A must be the expected bigger result and condition B the expected smaller result. i.e. if you expect aggression to increase in a warm classroom, and decrease in a cold classroom, you would expect warm classroom to have a bigger aggression score and so this would be condition A. Warm classroom, condition A GRAPH You must display your results in an appropriate graph. Only one graph is required. You must interpret your graph, i.e. What does it show? Are the scores higher in one condition? How much are they higher by? Are there any outliers? Etc. INFERENTIAL STATISTICS The appropriate measure of statistical significance depends on: 1) Test of difference or correlation 2) Level of data 3) Whether the data is related (repeated measures) or unrelated (independent groups) It will either be a related t-test or an unrelated t-test depending on whether you have used repeated measures or independent groups respectively. INFERENTIAL STATISTICS You must first justify why you have chosen your statistical test. You need to explain the conditions under which the test is used (Hint! This is explained on the previous slide!). Also explain that although the criteria for a parametric test are not met (data is normally distributed), these tests are very robust. Working out of the t-test must be present in the appendices INFERENTIAL STATISTICS You must now explain the level of significance that has been used. The p<0.05 level is used as it is the conventional level of significance that is accepted by psychologists. P<0.05 means that there is a 95% chance that the results occur due to an effect of the IV on the DV, and a 5% chance that the results occur due to random variability. The ‘p’ stands for ‘probability’ INFERENTIAL STATISTICS You must then interpret your stats test results using a ‘numerical statement of results’. This should include: Calculated t value Critical value No. of Participants (N) Directional/ non-directional hyp Level of significance Whether the null hypothesis is retained or rejected See the next slide or the VTLE results section for help with this NUMERICAL STATEMENT OF RESULTS EXAMPLE The calculated value from the related/unrelated t-test was __. This is less than/ more than the critical value of __ for a directional/ non-directional (1 tailed/ 2 tailed) hypothesis when N = __. This shows that the risk that this difference occurred by chance is more than/ less than 0.05 or 5%. The result is therefore significant/ nonsignificant and the null hypothesis can be rejected/ retained. (t=_,N=_, CV _, p<0.05). POINTS TO REMEMBER! Explain and interpret your results in detail Be consistent in calling your conditions ‘A’ and ‘B’ Adopt a consistent approach throughout the section Don’t include any workings out. These must appear in the appendix (see ‘additional important resources’)