Presentation Transcript

1. Quantitative and Psychometric Methods PSY 302

   William P. Wattles, Ph.D. Spring 2014
2. My goal For you to leave this class with life changing skills and knowledge.
3. Successful students
4. Science Begins with Counting.
5. Peter Medawar science — ‘ incomparably the most successful activity human beings have ever engaged upon’.
6. Chance Happens Died July 4, 1826.
7. Medellin, Colombia
8. Carpenters use hammers.
9. Psychologists use statistics
10. Psy 302 E-mail:  wwattles@fmarion.edu Web page:  http://fpweb.fmarion.edu/wWattles/psy302/
11. First Homework Send me an e-mail. Put PSY302 first on the subject line Give me a 4-digit code to use to post your grade. Complete two nonsense quizzes and give me your two scores for each test. Also send me a picture and an example of chance in your life.
12. Homework All homework submitted via e-mail Adhere to deadline to get credit Homework returned for correction is not credited unless the corrections are made. 16 assignments
13. National Institute on the teaching of Psychology
14. Texts Statistics for the Behavioral Sciences http://www.sagepub.com/priviterastats/main.htm
15. Psychology The sciencethat deals with mental processes and behavior.
16. Human Behavior Individual differences Predict Understand Change
17. Fixation of Belief -Peirce method of tenacity Method of authority a priori method method of science
18. The Scientific Method empirical: a. Relying on or derived from observation or experiment: “empirical results that supported the hypothesis.” b. Verifiable or provable by means of observation or experiment: empirical laws others can arrive at the same results.
19. Empirical Example New York Times in class
20. Empirical Example
21. Individual Differences Variations in the psychological variables between organisms
22. Individual Differences We rarely or never find absolute results.
23. Uncertainty Statistics describe uncertainty.
24. Individual differences People vary in their ability to learn. Some learn quickly with little effort Some learn slowly with much effort
25. Don’t put yourself down You can pass this course. Must work daily. Prepare for class Attend class Review Do Homework
26. Statistics Statistics: The science of gaining information from numerical data. Data: numbers with a context. Collections of measurements for objects. Data analysis: using numbers and graphs to make sense of data Data Production: methods for collecting “good” data.
27. McDonald’s Names U.S. Chief as Its No. 2 Executive He did it by focusing on quality not quantity, expanding menu offerings, and improving customer satisfaction and efficiency. 
28. Descriptive versus Inferential Descriptive statistics: methods used to describe the data that has been collected. Inferential statistics: estimating population parameters based on sample statistics.
29. Descriptive Statistics McDonald’s sales for the period that ended Nov. 30 were up 2.8 percent in the United States and 3.9 percent companywide. Mr. Thompson would oversee operations at McDonald’s nearly 32,000 restaurants worldwide. The company operates in more than 117 countries.
30. Descriptive Statistics  Wendy’s world's third largest hamburger fast food chain with approximately 6,700 locations following McDonald's 31,000 locations and Burger King's 11,200 locations.
31. Inferential statistics Students in Fall 2003 liked the New York Times, I infer others will Obama and Clinton both won 33% in the national poll, which was conducted after the Illinois senator's decisive win in the Iowa caucus
32. Sampling Error True Population Mean 74.4
33. The results of the experiment were that the average height of the plants of variable group A was greater than that of the other variable groups.  What’s the problem with his conclusion? ______ _______ Jonathan A. 7th Grade Selah Intermediate School
34. Capitalizing on Chance One day in January it was colder in Florence, SC than in New Vineyard, Maine.
35. Inferential Statistics Population: a group of objects or individuals that can be measured Individuals: the objects described by a set of data. Individuals may be people, animals or things Sample: a sub-group of objects subjects or individuals.
36. Population Sample
37. Characteristics of data Parameter: measurable characteristic of a population. A number that describes the population Statistic: measurable characteristic of a sample. A number that describes the sample and can be computed from sample data.
38. PopulationParameter SampleStatistic
39. Variables Variable: any characteristic of an individual. Can take different values for different individuals. Variables can be quantitative or categorical
40. Two types of variables categorical or qualitative Something that falls into one of several categories. What can be counted is the count or proportion of individuals in each category. Example: Your blood type (A, B, AB, O), your hair color, your ethnicity, whether you paid income tax last tax year or not.
41. Two types of variables quantitative or measurement Something that can be counted or measured for each individual and then added, subtracted, averaged, etc., across individuals in the population. Example: How tall you are, your age, your blood cholesterol level, the number of credit cards you own.
42. Ways to chart categorical data Bar graphsEach category isrepresented by a bar. Pie chartsThe slices must represent the parts of one whole.
43. Histogram to chart Measurement Data The range of values that a variable can take is divided into equal-size intervals. The histogram shows the number of individual data points that fall in each interval.
44. How do you decide if a variable is categorical or quantitative? What is being recorded about the individuals? Is that a number (quantitative) or a statement (categorical)? Homework Lindsay Elizabeth #1 Lindsay Nicole #2 Flower quiz Amber 45 Alisha 150
45. Example CategoricalEach individual is assigned to one of several categories QuantitativeEach individual is attributed a numerical value
46. 935,935 workers on U.S. soil Emmit Smith wears number 22 Education is largest department, business is second My cabina in Costa Rica cost 2500 colones. Miriam is 5 feet 4 inches tall Tom is the tallest person at his work I live at 419 Park Avenue Wednesday’s most active stock was AT&T AT&T traded 5,416,700 shares Examples
47. Review so far Psychology as a science requires empirical observation to support our hypotheses. Data are numbers that represent our observations. We use inferential statistics to draw conclusions about a population based on a sample. Chance can lead to misleading data

48. Picturing Distributions with Graphs

    Chapter 1
49. Data example What type of variable?
50. Data example What type of variable? Per cent
51. Frequency Distribution The most common graph of the distribution of one quantitative variable is a histogram
52. Frequency Distribution Concerned with frequency of values of one variable called X Represented by histogram or density curve The levels of the variable on the horizontal axis and frequency on the vertical axis. Symmetrical distributions described by mean and standard deviation
53. Distribution All the values a variable can take and how often each occurs.
54. Describing a distribution Center: where is the middle of the data? Spread: is the data tightly bunched or spread out? Shape: is the data symmetrical? Outliers: Are there extreme values which may suggest an error or require a special explanation?
55. Histograms Used for: A Measurement Data B Qualitative Data C Categorical Data D. All of the above
56. Bar graph Categorical Data Also called: A. Qualitative Data B. Measurement Data C. Data Data D. Quantitative Data
57. Homework Grade on web Credit for a “reasonable effort” Help menu Do what you can Must make corrections if I return it.
58. Frequency Distribution Concerned with frequency of values of one variable called X Represented by histogram or density curve The levels of the variable on the horizontal axis and frequency on the vertical axis. Symmetrical distributions described by mean and standard deviation
59. Distribution All the values a variable can take and how often each occurs.
60. Describing a distribution Center: where is the middle of the data? Spread: is the data tightly bunched or spread out? Shape: is the data symmetrical? Outliers: Are there extreme values which may suggest an error or require a special explanation?
61. Graphing Literacy http://www.psychologicalscience.org/observer/getArticle.cfm?id=2550
62. Graph check-list Is there a clear, specific title? Do both axes have labels? Are all terms the same as in the text? Are the units of measurement included? in the title or data labels? Do the values on the axes go down to zero? Are colors used in a simple, clear way? Has all chartjunk  been eliminated?
63. The End The End