Psych 230 Psychological Measurement and StatisticsLast Time….This Time….Statistical TestingStatistical tests (so far)So farSo Far ContinuedSo Far continuedIntroduction to experimental methodsSlide 10Slide 11Hume’s CriteriaExperimental MethodsExperimental MethodsExperimental MethodTodaySlide 17Two Sample T-TestSlide 19Slide 20Slide 21Slide 22Assumptions of the Two Sample T-TestSlide 24Slide 25Slide 261. State the HypothesesSlide 282. Decide which test to use3. Calculate tobtPlotting the difference between 1 and 2Slide 32Real differencesSlide 34Slide 35Slide 36Slide 37Slide 38Slide 39Slide 40Slide 413. Calculate TobtSlide 43Slide 44Slide 45Slide 46Slide 47Slide 48Slide 49Slide 504. Calculate the critical valueTcrit and Tobt5. Make our ConclusionAnother exampleSlide 55Slide 56Slide 57Slide 58Slide 59Slide 60Slide 61Slide 62Slide 63Slide 64Slide 65Slide 66Cause and EffectThe EndSlide 69Related Samples T-TestSlide 71Slide 72Example - Related Samples T-Test1. Decide which test to use2. State the HypothesesSlide 76Slide 77Slide 78Slide 79Slide 80Slide 81Slide 82Slide 83Slide 84tcrit and tobtSlide 86Psych 230Psychological Measurement and StatisticsLast Time….•Hypothesis testing reviewed•Statistical Errors reviewed•Z-test reviewed•One sample T-TestThis Time….•Reporting statistics•Two sample T-Test•For Independent samplesStatistical Testing1. State the hypotheses (H0 and H1)2. Decide which test to use 3. Calculate the obtained value4. Calculate the critical value (size of )5. Make our conclusionStatistical tests (so far)•The statistical tests we have used so far concentrate on finding whether a sample is representative of a known population•Two characteristics of these tests:–one sample is drawn–we know the population mean•Z-test–we also know the population variance•T-test (one sample)–we do not know the population varianceSo far•Hardly any of these tests are used in psychological research.•They were used to introduce you to the logic behind statistical testing.–Incrementally.•The z-test showed us how to test the likelihood a sample came from a population where we know  and xSo Far Continued•Rarely do we know both of those population parameters.•It did introduce you to critical values of a statistical test and what they mean.•Next we learned how to do a single sample t-test.•Again this test is not used often in psychological research–Rarely do we know the population parameter So Far continued•Even though it isn’t used much, it did introduce you to the t distribution.•From now until the end of this course we will be learning about statistical tests which are used in this field.•These statistical tests are useless without the methods that go with them.Introduction to experimental methods•Over the next few lectures we will be covering statistics which are used for various types of experiments.Introduction to experimental methods•Over the next few lectures we will be covering statistics which are used for various types of experiments.•What is an experiment?Introduction to experimental methods•Over the next few lectures we will be covering statistics which are used for various types of experiments.•What is an experiment?•It is a research tool which helps scientists infer causality.•The method is born from the criteria set by a philosopher named David HumeHume’s Criteria•A cause must precede effect•A cause and effect must be spatially and temporally contiguous–The cause and the effect touch.•A necessary connection between cause and effect.–Without cause you don’t see the effect.Experimental Methods•John Stewart Mill expanded on this and proposed various methods. –The method of his which is most closely related to experimental methods is his Method of Difference. •An experimenter takes two groups which are identical in every respect except for one thing and the effect is present after the introduction of that one thing, that one thing is the cause.•The Experimental methods try to simulate conditions which approximate these three criteria.Experimental Methods •For example let’s take the simplest experiments.–Experimenters randomize the participants–Why do they do that? They randomize the participants for the two groups in order to try to eliminate effects due to individual differences. •In other words individuals have a multitude of other causes for their behavior.–These other causes are called error.–Since error is random and if the assignment to conditions is random then the errors in one group on average should cancel out the errors due to individual differences in the other group.•Randomization helps satisfy Hume’s third criteria by making the two groups as identical to each other as possible when it comes to individual differences.Experimental Method•Control of the independent variable is also a necessary component of a true experiment.–By having control of the independent variable the experimenter can try to come close to meeting the standards outlined by Mill.Today•The first statistic along with the corresponding method is a bivalent experiment with unrelated groups.–Unrelated groups means that the individuals in the control condition are not the same individuals in the experimental condition.•The corresponding statistic is the two sample T-Test with unrelated groupsTwo Sample T-testTwo Sample T-Test•Important!•Make sure you understand:–What a dependent variable, an independent variable and a condition areTwo Sample T-Test•The tests we have used so far assume that we know the population mean of the variable we are interested in•We compared a sample to the population to see if this sample is “representative” of the population•None of these really help us when it comes to inferring cause in an experimental setting. –The population is not identical to the experimental group or sample in every way but the independent variable.•In most psychological experiments though, we simply do not know what the population scores are–Experiment: We want to know if the degree of friendliness of wait staff in a restaurant (very friendly or not friendly) affects the size of tips•How to conduct this experiment?Two Sample T-Test•Before, we compared a sample to the population •Now, we compare one sample to another sample •In this experiment, we wish to compare the performance of two groups (friendly vs. non-friendly)–we instruct