# Lab Report Assignment

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Notes on measures used 4. Statistical analyses – general information A Quick Guide to Interpreting t-tests and Pearson”s r (Significance Testing) 6, Topic I – outline, readings, statistical analyses …. Pi 7. Topic 2 – outline, How readings, statistical analyses to Approach this Task (Some Suggestions) a) Choose a topic that you understand b) Read through the data sheet (online) and the Notes on Measures section (this document) to remind yourself of the information that was gathered. C) Skim read the suggested Readings for your topic to find information relevant to your topic.

If a section is not relevant, skip it. The reference lists of the articles may contain other useful articles to follow up, and a library database search may be helpful. Focus on the major ideas in the area first – details can come later. D) Read through the Statistical Analyses (this document) for your topic. For each graph or analysis, ask yourself M/hat is this statistic}graph telling me? ” e) Write your hypotheses. These should follow logically from the literature on your topic AND be testable using the analyses you have available.

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In real life, you normally know your research question before you begin gathering data. In this assignment, however, o may need to work backwards: look at the data that have been gathered and, in consultation With your reading, consider What question the data can answer for you. By the end of the Introduction, your reader should understand: General topic under investigation and why it is worth investigating CLC Relevant theories and evidence: L] What theoretical ideas have been applied to this area? What empirical studies (if any) have been done in this area?

I:] Can we trust the results or previous studies? (i. E. Were their research methods sound? ) O What questions remain unanswered? Try to link these to the present study! ) [l Aim and specific hypothesis of present study. (There may be more than one. ) 0 For an open-ended exploratory study, state your aim: e. G. Discover whether there is a relationship between X and Y’. M. However, if you have reasons for expecting a particular outcome, state your hypothesis "From Oblongs; (2001) theory, it is predicted that X scores will be significantly higher than Y scores. Method. The purpose of this section is to describe how your data were gathered in enough detail for other researchers to replicate, and to justify using the methods we did. Participants: use the information from Statistical analyses – General information to summaries the characteristics Of your sample. Note that data have been pooled across classes. Materials/Apparatus: Briefly describe the tests and other materials relevant to your topic. Do not describe the other tests/tasks you did which are unrelated to your topic.

Indicate what hypothetical construct each of the materials was intended to measure. Do not describe in this section what you did with the measures, Procedure: Outline, step by step, how the data were gathered in your tutorial lass, Include instructions to participants (these do not have to be verbatim) and any time limits. You should also mention any steps that were taken to control for potential confounds. Your reader should have sufficient information to replicate your study (i. E. , rill it again tort themselves).

Describe how tests and tasks were scored. By the end of the section, your reader should be equipped to understand what the scores mean on various measures so that the Results section will make sense, Results: This section presents a summary of your findings, and the process you went through to analyses your data. Results sections use statistics, often presented in tables and/or figures, to summaries the findings and whether or not they were significant” (See Statistical Analyses -? General information section for more on this. Results sections also include sufficient text to explain why each particular analysis was carried out, to guide your reader’s attention to the important points to note from a table or figure, and to indicate briefly feather the results fitted With predictions. Try to Structure your Results section to tell a coherent story. The first step in data analysis should ALWAYS be to check your data for Oddities – i. . , people With missing data, impossible scores, extreme scores, frequency distributions that vary wildly from normality etc.

Inform purr reader Of the Steps taken to ensure the data were "clean” before testing any hypotheses. You have been provided with histograms and shatterproof to help you check for potential problems. The next step is to test your hypotheses. Make sure that you present both descriptive and inferential statistics (e. G. , "Extravert’s made significantly more responses than introverts, Ms 8. 00, 4. 25, respectively, t(24) = 2. 31, p L] Briefly summaries the results in relation to your aims and hypotheses 2 Discuss how consistent your findings are with the findings of previous studies Discuss methodology, and any strengths or weaknesses of your study Remember the difference between The World of Ideas (the psychological constructs you were hoping to manipulate or measure) and The World of Observations (the concrete, observable things you actually did). Are there any reasons to think that the actual manipulations or measures you used might (or might not) map well onto their theoretical counterparts?

C What alternative explanations can you think of for your results? Can any be ruled out? C] Sometimes it is helpful to divide weaknesses into: I) possible confounds (limitations to internal validity) -? these are systematic factors that make the interpretation of your results ambiguous (e. G. , if you are comparing left-hander’s to right-hander’s and it just so happens that in your sample all left-hander’s are male and all right-hander’s are female, then handedness is confounded with gender and we cannot tell whether differences between groups are due to handedness or gender. These factors can make it appear that your hypothesis has been met (or not met) but this may be for the rang reasons. 2) sources Of random error – unsystematic factors that make data messy (e. G. , some participants receiving slightly different instructions from others, testing taking place at different times in different places). These factors generally make it harder to find statistically significant results. 3) external validity – issues to do With how far we can generalize from our study to Other populations/tasks/ situations. Discuss the implications of your findings for theory, bearing strengths and weaknesses in mind.

Have you found support for someone’s theory? Have you falsified it? Have you found that things are not as simple as their theory suggested? This is a good time to re-read your Introduction and link your new findings back to the points you made there. Make suggestions for future research (i. E. , unanswered questions), Avoid vague, blanket statements such as “Clearly, more research needs to be done. ” Tell your reader exactly what needs to be done. Draw conclusions for your reader that relate to the general topic outlined at the beginning of Introduction.

References: See The Publication Manual of the American Psychological Association in Reference section of library for correct style. For a quick guide to PAP style, see Burton (2010), or Jackson (2009). Brief PAP style guides are also available online. Your References section should contain a complete list of all papers cited in the main text, but should Only include papers that have actually been cited in the main text of your lab report. њ References should cover theoretical background, relevant empirical findings, information on tasks and tests used.

Journal of Personality and Social Psychology, 67, 319-333. ) Jorum, A. F. , Christensen, Huh, Henderson, A. S. , Comb, P. A. , Sorter, A. E. And Rodgers, B. (1999) using the IBIS/BAS scales to measure behavioral inhibition and behavioral activation: Factor structure, validity and norms in a large community sample. Personality and Individual Differences, 26, 49 – 58. Proverbs-based personality Questionnaire This questionnaire is designed to measure aspects of personality according to endorsement of particular proverbs.

It has 44 items measuring S different dimensions of personality: Z] Machiavellian: tendency to be self-centered, antisocial, alienation Is Restraint: tendency to be cautious, careful, diligent Enjoys Life: tendency to take advantage of opportunities to enjoy life Achievement Striving: tendency to be achievement oriented Group Ties: tendency to be family and home focused All trait scores range from I(low) – 5 (high). Has, H. , & Rouse, S. (2012). If it walks like a duck: Construct validation of rovers-based personality dimensions. Personality and Individual Differences, 52, 458-461.

Statistical Analyses – General Information The statistical analyses and graphs in this document are based on the data that we gathered in weeks 2 and 3. The information provided here will allow you (a) to describe the demographic characteristics Of your sample in your Method section, (b) to test hypotheses related to your topic, and also (c) to conduct data checks to ensure that your results are not misleading due to outliers or statistical assumption violations. (See A Quick Guide to Interpreting t-tests and Pearson”s r for more on this.

Read through all the analyses for your topic and be sure that you understand what they are telling you. However, you are not required to present everything in your lab report. Statistics directly related to testing your hypotheses should be presented in the Results section of your lab report. You should also describe in your Results section any steps that were taken to check data and assumptions (e. G. , checking histograms or shatterproof for outliers) and what was done (if anything) to fix any problems, but you do not need to include histograms or detailed descriptions of what all the frequency distributions looked eke.

Please note that this computer printout is not presented in PAP style, but your lab report should be in PAP style or penalties will apply, You will need to construct your own summary tables and graphs for your Results section. Please present your statistics rounded to two decimal places. Tables and Graphing The statistics provided here will give you the information required to construct bar graphs or summary tables but you do not have the information required to draw your own histograms or shatterproof. Instructions on constructing bar graphs in Excel are available from the SAYS 73 website.

If you identify a problem room a scattered or histogram and wish to report it, for this assignment you may refer to the graph by number in your text without including the physical graph itself in your assignment (your tutor will have the computer output to refer Information about the sample A total of 78 data sheets were submitted in time for processing. Because some people did not report responses to some measures, N varies across different analyses. Descriptive Statistics Minimum Maximum Statistic age Valid N (likewise) 19. 00 50. 0 Mean Median SST. Deviation Keenness 25. 5195 24. 00 6. 51238 1. 7204 Kurtosis 2. 9155 Frequency Valid Total female Missing male System A Quick Guide to Interpreting t-tests and Person’s r (Significance Testing) We will cover the logic of these statistics in detail in lectures. This quick guide will help you to interpret your findings straight away. What is significance testing? The purpose Of inferential statistics, such as t-tests and Pearson”s r, is to decide whether or not a particular finding is statistically significant.

That is, whether the finding is so unlikely to have happened by chance that we are allowed to be excited about it and treat it as real; in our lab report. What is a t-test? Tests are used to test whether two means are significantly different from each other. T-tests need to be interpreted together with the relevant means. There are three kinds of t-test. Only one kind appears in these lab topics: Independent samples t-tests compare the means from two separate samples on the same measure. (e. G. Topic 1 – comparison of 2 groups on PANDAS Positive) What is Pearson”s correlation (Pearson”5 r)?

Pearson”s r tests whether there is a significant linear association between two variables. That is, as scores on one variable increase, do scores on the other variable also increase (or decrease) systematically? E. G. , in Topic 2, as a people”s Neurotics scores increase, do their working memory scores decrease? ) Pearson”s r can take any value between -1 and +1. Positive r values tell you that as scores on one variable INCREASE, scores on the other variable INCREASE. Negative r values tell you that as scores on one variable INCREASE, scores on the other variable DECREASE.

A zero r value tells you that there is no linear association at all between the two variables – high scores on One variable tell us nothing about Whether scores on the other variable will be high or low. R values from O – . 3 are considered WEAK correlations values from . 4 – . 6 are considered MODERATE correlations r values from . 7 -? I . 00 are considered STRONG correlations HOW do tell Whether t (or r) is significant? Each t. Test and Person’s r result has a Sigh. (2. Tailed)” value next to it. If the Sigh value is LESS than 0. 05, then the result is SIGNIFICANT If the Sigh value is GREATER than or equal to 0. 5, then the result is NOT SIGNIFICANT. If a t. Test is SIGNIFICANT then we are allowed to treat the difference between the means involved as real and not accidental. If a t-test is NOT SIGNIFICANT then any difference between the means may just be an accident. It a Pearson correlation is SIGNIFICANT then we are allowed to treat the association between the variables involved as real and not accidental. If a Pearson correlation is NOT SIGNIFICANT then any association between the variables may just be an accident, How do report t-test results in my lab report?

You need to report three pieces of information from the analysis tables: the t, UDF, and Sigh. In PAP style, we write p (for probability) rather than Sigh (for significance). P and Sigh. Refer to the same thing. For a SIGNIFICANT t-test result (e. G. Fit – 5. 22, UDF = 238, Sigh. = . 000) write: “The t-test was significant, t(238) = 5. 2, p YOU need three pieces Of information from the analysis tables: the Pearson correlation (r), N, and Sigh. In PAP style, we write p (for probability) rather than Sigh (for significance). P and Sigh. Refer to the same thing. You then need to convert N to UDF (degrees of freedom). For Person’s r, UDF N. 2. For a SIGNIFICANT r result (e. G. R- 0. 80, N – 100, Sigh. -000), calculate UDF = 100-2 = 98. Write: “Pearson”s r was positive and significant, r(B) = 0. 80, p . 05” For a NON. SIGNIFICANT r result (e. G. R 0. 06, N – SO, Sigh. – . 674), calculate UDF = 50-2 = 48. Write: “Person’s r was not significant, r (48) = 0. 6, p . 05” How do I tell whether the data are safe to use for t-tests and Pearson correlations? Data should be free from extreme outliers and at least approximately normally distributed. It not, the results from t-tests and r should be treated with caution because they may be misleading. If you detect a problem but are not able to do anything about it, note it in purr lab report and be duly cautious in your interpretation, Topic I The influence of personality on the experience of positive and negative affect There is extensive research suggesting that personality is important in predicting emotion and mood states.

For example, many studies (e. G. ) suggest that extroversion is related to positive emotions such as happiness and neurotics is related to negative emotions. In this study, we are combining these ideas and testing whether people who have higher levels Of extroversion and lower levels Of neurotics (Stable extravert’s) are significantly different from people who have rower levels Of extroversion and higher levels Of neurotics (Neurotic Introverts) in their experience of positive and negative affect over the past week.

We have done this by splitting the scores on the Extroversion and Neurotics scales at the median, thereby dividing them into different four groups. This can be expressed in the diagram below. High E Stable extravert’s: High on Extroversion Low on Neurotics Low N High N Neurotic Introverts: High on Neurotics Low on Extroversion Low E TO supplement this, we Will also kick at the relationship between the Other measures of personality (Agreeableness, Openness, and Conscientiousness) and he experience Of positive and negative affect/mood.

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