Quantitative and Psychometric Methods PSY 302

William P. Wattles, Ph.D.

Spring 2014

My goal

• For you to leave this class with life changing skills and knowledge. 2

Successful students

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Science Begins with Counting.

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• science — ‘ incomparably the most successful activity human beings have ever engaged upon’.

Peter Medawar

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Chance Happens

Died July 4, 1826.

Died July 4, 1826.

Medellin, Colombia

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Carpenters use hammers.

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Psychologists use statistics

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Psy 302

• • • • E-mail: [email protected]

Web page: http://fpweb.fmarion.edu/wWattles/psy302/ 10

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. 11

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 12

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National Institute on the teaching of Psychology

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• • Statistics for the Behavioral Sciences http://www.sagepub.c

om/priviterastats/main .htm

Texts 15

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• The

science

that deals with mental processes and

behavior

.

Psychology

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• Individual differences – – – Predict Understand Change

Human Behavior

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Fixation of Belief -Peirce

• • • • method of tenacity Method of authority a priori method method of science 20

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.

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• New York Times in class

Empirical Example

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60% 50% 40% 30% 20% 10% 0% 42% Yes

Empirical Example

New York Tim es in Class

48% 9% No

Answ er

Yes but 23

Individual Differences

• Variations in the psychological variables between organisms 24

Individual Differences

• We rarely or never find absolute results.

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• Statistics describe uncertainty.

Uncertainty

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Individual differences

• People vary in their ability to learn.

– Some learn quickly with little effort – Some learn slowly with much effort 27

Don’t put yourself down

• • • • • • You can pass this course.

Must work daily.

Prepare for class Attend class Review Do Homework 28

Quizzes 10% Paper 10%

Semester Points

Homework 15% Three exams 45% Final Exam 20% 29

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.

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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.

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Descriptive versus Inferential

• •

Descriptive statistics

: methods used to describe the data that has been collected.

Inferential statistics

: estimating population parameters based on sample statistics.

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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.

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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.

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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 35

kaitlin s 68.3

70.3

michelle a 70.7

Katrina 71.0

megan Rachel 71.0

71.3

laquanda 71.7

eric 72.0

katie tracy allie 72.7

73.0

74.0

Q tiffany kristina christain 74.0

74.3

74.7

76.7

amanda shannon latoya aona 76.7

77.0

81.3

84.3

Sampling Error

• • True Population Mean 74.4

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Jonathan A. 7 th Grade Selah Intermediate School

• • • 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?

______ _______ 37

Capitalizing on Chance

• One day in January it was colder in Florence, SC than in New Vineyard, Maine. 38

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.

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Population Sample

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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.

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Population Parameter Sample Statistic

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Variables

• Variable: any characteristic of an individual. Can take different values for different individuals.

• Variables can be quantitative or categorical 43

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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.

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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.

Ways to chart categorical data

–

Bar graphs

Each category is represented by a bar.

–

Pie charts

The slices must represent the parts of one whole.

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.

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

Example

Individuals in sample

Patient A Patient B Patient C Patient D Patient E Patient F Patient G

Categorical

Each individual is assigned to one of several categories

DIAGNOSIS

Heart disease Stroke Stroke Lung cancer Heart disease Accident Diabetes

Quantitative

Each individual is attributed a numerical value

AGE AT DEATH

56 70 75 60 80 73 69

Examples

• • • • 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 51

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 52

Picturing Distributions with Graphs

Chapter 1 53

Data example

• What type of variable?

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Data example

• What type of variable?

• Per cent 55

Frequency Distribution

• The most common graph of the distribution of one quantitative variable is a histogram 56

Frequency Distribution

u Concerned with

frequency

of values of

one variable

called X u Represented by histogram or density curve u The levels of the variable on the horizontal axis and frequency on the vertical axis.

u Symmetrical distributions described by mean and standard deviation 57

Distribution

• All the values a variable can take and how often each occurs. 58

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?

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Histograms

• • • • • Used for: A Measurement Data B Qualitative Data C Categorical Data D. All of the above 62

Bar graph

• • • • • • Categorical Data Also called: A. Qualitative Data B. Measurement Data C. Data Data D. Quantitative Data 63

Homework

• • Grade on web Credit for a “reasonable effort” – Help menu – Do what you can • Must make corrections if I return it.

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Frequency Distribution

u Concerned with

frequency

of values of

one variable

called X u Represented by histogram or density curve u The levels of the variable on the horizontal axis and frequency on the vertical axis.

u Symmetrical distributions described by mean and standard deviation 68

Distribution

• All the values a variable can take and how often each occurs. 69

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?

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Graphing Literacy

• http://www.psychologicalscience.org/obser ver/getArticle.cfm?id=2550 71

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?

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The End

The End

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