The Research Skills exam: The four horsemen of the apocalypse: pestilence, war, famine and the RS1 exam.

Slides:



Advertisements
Similar presentations
The Research Skills exam: The four horsemen of the apocalypse: pestilence, war, famine and the RS exam.
Advertisements

CHAPTER TWELVE ANALYSING DATA I: QUANTITATIVE DATA ANALYSIS.
Ordinal Data. Ordinal Tests Non-parametric tests Non-parametric tests No assumptions about the shape of the distribution No assumptions about the shape.
Statistical Tests Karen H. Hagglund, M.S.
Some statistics questions answered:
Basic Statistical Review
The t-test:. Answers the question: is the difference between the two conditions in my experiment "real" or due to chance? Two versions: (a) “Dependent-means.
Research Skills- Summer Term Practical classes run in weeks 2,3,4 (& 5 for those of you who miss a class on Mon wk 4 due to the Bank Holiday…)
Statistical Analysis SC504/HS927 Spring Term 2008 Week 17 (25th January 2008): Analysing data.
Today Concepts underlying inferential statistics
Data Analysis Statistics. Levels of Measurement Nominal – Categorical; no implied rankings among the categories. Also includes written observations and.
Summary of Quantitative Analysis Neuman and Robson Ch. 11
Inferential Statistics
Choosing Statistical Procedures
Understanding Research Results
Review I volunteer in my son’s 2nd grade class on library day. Each kid gets to check out one book. Here are the types of books they picked this week:
AM Recitation 2/10/11.
Estimation and Hypothesis Testing Faculty of Information Technology King Mongkut’s University of Technology North Bangkok 1.
Hypothesis Testing Charity I. Mulig. Variable A variable is any property or quantity that can take on different values. Variables may take on discrete.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Bivariate Relationships Analyzing two variables at a time, usually the Independent & Dependent Variables Like one variable at a time, this can be done.
Covariance and correlation
Descriptive Statistics e.g.,frequencies, percentiles, mean, median, mode, ranges, inter-quartile ranges, sds, Zs Describe data Inferential Statistics e.g.,
Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 17 Inferential Statistics.
Introduction To Biological Research. Step-by-step analysis of biological data The statistical analysis of a biological experiment may be broken down into.
Special Topics 504: Practical Methods in Analyzing Animal Science Experiments The course is: Designed to help familiarize you with the most common methods.
Statistics 11 Correlations Definitions: A correlation is measure of association between two quantitative variables with respect to a single individual.
Descriptive Statistics
T-TEST Statistics The t test is used to compare to groups to answer the differential research questions. Its values determines the difference by comparing.
Statistical Analysis. Statistics u Description –Describes the data –Mean –Median –Mode u Inferential –Allows prediction from the sample to the population.
Hypothesis of Association: Correlation
Descriptive Statistics
Chapter 14 Nonparametric Tests Part III: Additional Hypothesis Tests Renee R. Ha, Ph.D. James C. Ha, Ph.D Integrative Statistics for the Social & Behavioral.
FOUNDATIONS OF NURSING RESEARCH Sixth Edition CHAPTER Copyright ©2012 by Pearson Education, Inc. All rights reserved. Foundations of Nursing Research,
Chapter 12 A Primer for Inferential Statistics What Does Statistically Significant Mean? It’s the probability that an observed difference or association.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Chapter 9 Three Tests of Significance Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e.
Educational Research Chapter 13 Inferential Statistics Gay, Mills, and Airasian 10 th Edition.
Experimental Design and Statistics. Scientific Method
Chapter 13 CHI-SQUARE AND NONPARAMETRIC PROCEDURES.
Experimental Research Methods in Language Learning Chapter 10 Inferential Statistics.
Review. Statistics Types Descriptive – describe the data, create a picture of the data Mean – average of all scores Mode – score that appears the most.
Inferential Statistics. The Logic of Inferential Statistics Makes inferences about a population from a sample Makes inferences about a population from.
Testing Differences between Means, continued Statistics for Political Science Levin and Fox Chapter Seven.
Chapter 10 The t Test for Two Independent Samples
Chapter Eight: Using Statistics to Answer Questions.
Chapter 10 Copyright © Allyn & Bacon 2008 This multimedia product and its contents are protected under copyright law. The following are prohibited by law:
Introducing Communication Research 2e © 2014 SAGE Publications Chapter Seven Generalizing From Research Results: Inferential Statistics.
IMPORTANCE OF STATISTICS MR.CHITHRAVEL.V ASST.PROFESSOR ACN.
Biostatistics Nonparametric Statistics Class 8 March 14, 2000.
HL Psychology Internal Assessment
Internal assessment, Results, Discussion, and Format By Mr Daniel Hansson.
The Research Skills exam: The four horsemen of the apocalypse: pestilence, war, famine and the RS1 exam.
Chapter 13 Understanding research results: statistical inference.
Hypothesis Testing Procedures Many More Tests Exist!
Lecture 7: Bivariate Statistics. 2 Properties of Standard Deviation Variance is just the square of the S.D. If a constant is added to all scores, it has.
Educational Research Inferential Statistics Chapter th Chapter 12- 8th Gay and Airasian.
Nonparametric statistics. Four levels of measurement Nominal Ordinal Interval Ratio  Nominal: the lowest level  Ordinal  Interval  Ratio: the highest.
Educational Research Descriptive Statistics Chapter th edition Chapter th edition Gay and Airasian.
PSY 325 AID Education Expert/psy325aid.com FOR MORE CLASSES VISIT
Statistical principles: the normal distribution and methods of testing Or, “Explaining the arrangement of things”
Inferential Statistics Assoc. Prof. Dr. Şehnaz Şahinkarakaş.
Chapter 4 Selected Nonparemetric Techniques: PARAMETRIC VS. NONPARAMETRIC.
Data measurement, probability and Spearman’s Rho
Parametric and non parametric tests
Non-parametric tests, part A:
Some statistics questions answered:
The Research Skills exam:
Research Methods: Data analysis and reporting investigations.
COMPARING VARIABLES OF ORDINAL OR DICHOTOMOUS SCALES: SPEARMAN RANK- ORDER, POINT-BISERIAL, AND BISERIAL CORRELATIONS.
Presentation transcript:

The Research Skills exam: The four horsemen of the apocalypse: pestilence, war, famine and the RS1 exam.

 Week 11 ◦ Structure of exam ◦ Revisiting the flowcharts ◦ Section 1 & 3 of the Mock Exam  Week 12: ◦ Sections 5, 4, & 2 of the Mock Exam

The exam format: Two hours and five sections – Section 1: basic concepts Section 2: interpreting SPSS output. Section 3: which test? Section 4: pick a test and conclusions Section 5: write a results section

Be strategic: Don’t start at page 1 and work through. Each section carries equal marks. Answer all the easy questions first! Then tackle tricky stuff if there is time left.

 See Graham’s website…

PARAMETRIC OR NOT? Data type Ratio Interval Ordinal Nominal NON- PARAMETRIC Homogeneity of variance? SD 2 1/SD 2 2 > 2 Normal distribution? YesNo PARAMETRIC SD 2 1/SD 2 2 ≤ 2

 Frequencies = Chi-square  Looking at relationships = correlational  Looking at differences = experimental

Correlational – parametric & non-parametric  Pearson’s = parametric  Spearman’s = the other one

Experimental – parametric  Independent-measures t-test – independent measures design  Repeated-measures t-test – repeated measures design

Experimental – non-parametric, 2 conditions  Mann-Whitney – 2 different types of name, so independent  Wilcoxon – the other one, i.e., repeated

Experimental – non-parametric, 3 or more conditions  Kruskal-Wallis – independent design  Friedman’s – repeated design

Section 1: Basic concepts Ten multiple choice questions, testing knowledge of basic statistical concepts. Revise by writing clear definitions of terms such as "mean", "standard deviation", "normal distribution", "ratio data", "one-tailed test", etc. Read all of the five alternatives carefully, before making your choice.

1. The Standard deviation is: (a) a statistic that tells us how well our sample mean is likely to reflect the true, population, mean. (b) a statistic that tells us how scores are distributed around the mean of the set of scores. (c) a statistic that tells us whether scores are normally distributed. (d) a statistic that tells us what is the most commonly-occurring value in a set of scores. (e) none of the above. Correct definition [ b]

2. If the null hypothesis is true, then p <.05 means: (a) the obtained result is not due to chance. (b) the obtained result is a fairly important effect. (c) the obtained result is likely to occur by chance 95% of the time. (d) the obtained result is likely to occur by chance less than 5 times in a hundred. (e) the obtained result is likely to occur by chance 5 times in a hundred. Correct definition: [ d ]

Section 2: Interpreting SPSS output: Two parts: in each, you get SPSS output from a study, and 10 questions to answer about it.

Are there sex differences in car parking ability? An experimenter times how fast 9 women and 9 men can park their car. The data do not show homogeneity of variance.

1. Which is the most appropriate statistical test to perform on these data? (a) Wilcoxon matched-pairs test (b) Mann-Whitney test (c) Spearman's correlation test 2. The test results shown in the "Test Statistics“ table are all: (a) Statistically significant at p <.05 (b) Statistically significant at p >.05. (c) Not statistically significant at p <.05

1. Which is the most appropriate statistical test to perform on these data? (a) Wilcoxon matched-pairs test (b) Mann-Whitney test (c) Spearman's correlation test. 2. The test results shown in the "Test Statistics“ table are all: (a) Statistically significant at p <.05 (b) Statistically significant at p >.05 (c) Not statistically significant at p <.05

3. The standard error for the male group is: a)2.57 (=7.7/√9) b) 7.71 c) d) The standard deviation for the female group is: a)2.57 b)7.71 c)59.44 d)29.17

3. The standard error for the male group is: a)2.57 (=7.7/√9) b) 7.71 c) d) The standard deviation for the female group is: a)2.57 b)7.71 c)59.44 d)29.17

5. Complete the boxplot, using the data from the “descriptives” table. (Here, add median, and upper and lower whiskers representing the range).

Section 3: Which test: 10 questions. Each gives a brief description of a study that contains enough information for you to work out which test has been performed. Only ONE of the following tests will be correct: A. WilcoxonB. Spearman’s rho C. Friedman'sD. Pearson’s r E. Mann-WhitneyF. Chi-Squared G. Kruskal-Wallis

1. The statistics exam scores of three groups of students were recorded: group A had revised for 5 hours, group B for 10 hours and group C for 20 hours. The data do not show homogeneity of variance. What test is required to test the hypothesis that revision time affects exam performance? Test: [G (Kruskal-Wallis] 2. The number of students passing or failing a statistics exam in each of three groups of students was recorded: group A had revised for 5 hours, group B for 10 hours and group C for 20 hours. What test is required to test the hypothesis that revision time affects exam performance? Test: [F (Chi-square]

Section 4: Pick a test and conclusions Here are the instructions for this section: In the following questions you are given some details of an experiment, the results of a number of statistical tests, and a set of conclusions. Only ONE of these tests is appropriate, and only ONE in each set of conclusions is correct. Thus only TWO of the statements are correct in each of the following questions. Indicate which two are correct by writing the appropriate letters in the table at the end of this section. Look at the data; select the most appropriate test statistics; pick the correct conclusion for those results.

A researcher is interested in whether a drug affects appetite in rats. Eight rats were tested twice, once with the drug and once without the drug, in a random order. In order to feed, the rats need to climb a slope to get a food pellet, and the number of times each animal climbed the slope in a 5-minute period was recorded. The data are not normally distributed. Statistical tests: (a)Mann Whitney U (8,8) = 11.00, p =.03 (b)(b) Pearson’s r =.77, p =.02 (c) Spearman's rho =.80, p =.02 (d) Wilcoxon test: z = 2.52, p =.01 Conclusions: (e) The drug makes rats’ performance more variable (f) Rats climb the slope significantly faster after taking the drug (g) Rats climb the slope significantly more often after taking the drug (h) Rats climb the slope significantly less often after taking the drug Drug:No drug: M = 15.62M = SD = 4.03*SD = 3.01* *using n-1 SD formula

A researcher is interested in whether a drug affects appetite in rats. Eight rats were tested twice, once with the drug and once without the drug, in a random order. In order to feed, the rats need to climb a slope to get a food pellet, and the number of times each animal climbed the slope in a 5-minute period was recorded. The data are not normally distributed. Statistical tests: (a)Mann Whitney U (8,8) = 11.00, p =.03 (b)(b) Pearson’s r =.77, p =.02 (c) Spearman's rho =.80, p =.02 (d) Wilcoxon test: z = 2.52, p =.01 Conclusions: (e) The drug makes rats’ performance more variable (f) Rats climb the slope significantly faster after taking the drug (g) Rats climb the slope significantly more often after taking the drug (h) Rats climb the slope significantly less often after taking the drug Drug:No drug: M = 15.62M = SD = 4.03*SD = 3.01* *using n-1 SD formula

Section 5: Write a results section Read the scenario supplied; write a results section; interpret the results appropriately: The hypothesis is that revision combined with alcohol leads to better exam performance than revision alone. This was assessed by measuring participants' exam performance, after either 1) subjects had revised for 5 hours a week while drinking 500 ml of gin; or 2) simply revising for 5 hours each week. The results in terms of the exam scores are shown in the table below, together with the means, standard deviations, and results of the Mann-Whitney test used to compare the scores. RevisionRevision + gin M =12.75M = 9.13 SD = 4.23*SD = 3.76* (NB: maximum exam score is 20). U(8, 8) = 18.50, p =.161

(a) Graph the data in a form appropriate for inclusion in a lab report: This doesn’t have to be a work of art, but should be clear and labelled correctly. Include error bars and a title! Standard error = SD divided by square root of the number of subjects. Here, SEs are 1.40 (4.23 / square root of 8) for the sober revisers and 1.24 (3.76 / square root of 8) for the boozed ones.

(b) Describe the data in a form appropriate for inclusion in the results section of a lab report (assuming no graph in the results section). “A Mann-Whitney test was performed on these data. This revealed that there was no significant difference between the mean exam scores of subjects who combined revision with alcohol consumption (M = 9.12, SE = 1.33 sec) and those who revised without it (M = 12.75, SE= 1.50 sec), U(8, 8) = 18.50, p >.05. Exam performance is not significantly enhanced by combining revision with alcohol consumption."