Lect 10b1 Histogram – (Frequency distribution) Used for continuous measures Statistical Analysis of Data ______________ statistics – summarize data

Lect 10b2 Bar Graph: Used for ______________ measures

Lect 10b3 Descriptive statistics 2, 2, 3, 5, 5, 7, 8 Mean = _____ Median = ____ Mode = _____ 2, 3, 3, 4, 6, 7 Mean = _____ Median = _____ Mode = ____ Central tendency- _____ score  ______, ______, _____

Lect 10b4 Descriptive statistics 2, 2, 3, 5, 5, 7, 8 Mean = 4.57 Median = 5 Mode = 2, 5 2, 3, 3, 4, 6, 7 Mean = 4.33 Median = 3.5 Mode = 3 Central tendency- typical score  mean, median, mode

Lect 10b5 Measure of variability – how spread out are the scores 1. Range – difference between ________ and _______ score 1, 2, 9, 6, 9 Range? 2. ______________________ - square root of the variance (average squared deviation from the mean).

e.g., if the SD of scores on a test was 6.9 we can conclude that ____% of the class fell within plus or minus 6.9 points of the mean. 1 Standard deviation = 68% scores 2 Standard deviations = 95% scores 3 Standard deviations = 99.7% scores

Lect 10b7 Large amount of variability – _____ convinced of effect Little variability – _____ convinced of effect Measures of central tendency presented without measures of variability can be _______________!

Lect 10b8 Inferential Statistics  Most common method for analyzing data in studies using ______________ (Single-subject designs use _______ only)  ________ used to evaluate whether or not there is a functional relationship. p<_____ = suggests a functional relation Statistical significance never _____ a hypothesis, only shows that it isn’t _____

Lect 10b9 Inferential Statistics  Imagine you are doing a study with two groups. One gets treatment and one doesn’t.  There are differences across groups due to the IV (hopefully not a confound) – _______________________  Even if the IV had no effect, we would expect variability across groups due to sampling error and chance factors and variability within a group due to chance factors (_______ ___________)

Rat #Immediate Food Rat #Delayed Food M1 = 13.2M2= 17.6 SD = 1.9SD=2.1 How do tell whether this difference is a difference due to the IV or error? – Inferential statistics Rats in maze are given food for going the right way either immediately or after a delay.

Lect 10b11 Inferential Statistics Inferential statistics give you the probability of obtaining the difference in means you observed if there really was ___________________ The difference is judged significant if the probability is below α (_______), usually set to 0.05 Image from Introductory Statistics: Concepts, Models, and Applications David W. StockburgerIntroductory Statistics: Concepts, Models, and Applications

Lect 10b12 Null hypothesis  _______________in population means  Can either be _______ or ________  Rejecting the null means you support the ________________ hypothesis  P value = calculated probability of obtaining these data given the null is true. (The _______ the p value the better)  Obtain a p value of.05 means that there is a ___% chance that you would have obtained the results given that there really was ___ ____________ between the two groups

Lect 10b13 Inferential Statistics  Statistics for calculating significance usually compare: Test statistic = Between-group variance (M1-M2) Error variance (standard error) Rat maze example: t = -6.4/1.55 = (significant at the α =.01 level). Reject Null: Supports the hypothesis that reinforcer delay affects choice.

Lect 10b14 Errors in Hypothesis Testing  ________ error - “False alarm” There is ____ difference (Null is true) but We conclude that there _____ a difference (We reject null)  _________ error – “Miss” There ____ a difference (Null is false) but We conclude that there is ____ difference (We accept null)