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Jargon & Basic Concepts Howell Statistical Methods for Psychology

Jargon & Basic Concepts

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Jargon & Basic Concepts. Howell Statistical Methods for Psychology. Questions. Define and illustrate: Population, Sample Parameter, Statistic Descriptive, inferential statistics Random selection (sampling), assignment Internal, External validity Discrete, continuous variables - PowerPoint PPT Presentation

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Page 1: Jargon & Basic Concepts

Jargon & Basic Concepts

Howell

Statistical Methods for Psychology

Page 2: Jargon & Basic Concepts

Questions• Define and illustrate:

– Population, Sample– Parameter, Statistic– Descriptive, inferential statistics– Random selection (sampling), assignment– Internal, External validity– Discrete, continuous variables– Scale types (nominal, ordinal, interval,

ratio)

Page 3: Jargon & Basic Concepts

Population vs. Sample• Population – collection of all the objects

of interest to researcher (you). – College students, students at USF

• Sample – subset of objects from the population – Want a representative sample– Samples are relatively practical– Random samples have good properties– One person’s sample is another’s population

Page 4: Jargon & Basic Concepts

Parameter vs. Statistic

• Parameter – numerical summary of population– E.g., mean, standard deviation

• Statistic – numerical summary of sample– E.g., mean, standard deviation

• Typically we compute statistics and estimate parameters using statistics.

Page 5: Jargon & Basic Concepts

Descriptive vs. Inferential

• Descriptive statistics describe a sample– How tall are these students?

• Inferential statistics use sample statistics to make decisions about populations.– Is one method of instruction better than

another?

Page 6: Jargon & Basic Concepts

Random Select & Assign• Random selection is a process of picking a sample

from a population so that each element has the same probability of being sampled.

– E.g., lottery, every 3rd name from a list (this is actually a systematic sample but it’s good)

• Random assignment is assignment to treatment so that each element has an equal probability of being assigned to each treatment.

– E.g., lottery, every other name, etc.

• Both are typically accomplished by lists (aka frames) and computer generated numbers (e.g., SAS PROC PLAN)

Page 7: Jargon & Basic Concepts

Internal, External Validity

• Internal validity - quality of inferences about the study itself. Random assignment, history, maturation, etc.

• External validity – quality of inferences from the study to the larger domain of interest. Representative sample of participants, task relevance, behavioral consequents, etc. Aka generalizability of the results (but not generalizability study).

Page 8: Jargon & Basic Concepts

Variable & Distribution

• Variable vs. constant– Attribute either varies across objects or not

• Distribution: Collection of data

• Distribution: Array of scores– Height– Beck Depression Index– Rat bar press– Wonderlic

Page 9: Jargon & Basic Concepts

Discrete vs. Continuous

• Math– Integer vs. real numbers

• Data – Categorical vs. continuous (many valued,

ordered)

• ExamplesPolitical party, job satisfaction, response

time, country of origin

Page 10: Jargon & Basic Concepts

Scale types

• Nominal, ordinal, interval, ratio• Nominal – categories. No ordering; mean

has no connection to attributes• Ordinal – rank order only• Interval – rank order plus equal interval.

ratio of differences has meaning• Ratio – rank order, equal intervals,

rational zero point. Ratio of numbers has meaning.

Page 11: Jargon & Basic Concepts

Scale Types: Footrace reviewNominal Ordinal Interval Ratio

ID number Rank order of finish

Time of day of finish

Elapsed time from start

043 1 10:57 a.m. 4 min

011 2 10.59 a.m. 6 min

136 3 11:01 a.m. 8 min

112 4 11:02 a.m. 9 min

086 5 11:04 a.m. 11 min

Page 12: Jargon & Basic Concepts

ReviewFind a partner to work on this exercise.

Suppose you want to know whether one brand of tennis shoe is better than another. You have about $10K from a grant to study this. Describe a study you might conduct to find out. What might be your population, sample, independent and dependent variables? What statistics might you want to compute? Never mind the actual statistical test at this point. What data would you gather? What might a critic say about the internal and external validity of your study? What scale types are your IV and DV?