4632001 Tests and Measurements - PowerPoint PPT Presentation

1 / 47
About This Presentation
Title:

4632001 Tests and Measurements

Description:

The Course Outline is available through the Class Notes website. There is a ... the student must apply for aegrotat standing through the Registrar's Office ... – PowerPoint PPT presentation

Number of Views:59
Avg rating:3.0/5.0
Slides: 48
Provided by: hpcus552
Category:

less

Transcript and Presenter's Notes

Title: 4632001 Tests and Measurements


1
46-320-01Tests and Measurements
  • Intersession 2006

2
Course Highlights
3
Course Outline
  • The Course Outline is available through the Class
    Notes website
  • There is a course website
  • http//web2.uwindsor.ca/courses/psychology/hall6/i
    ndex.htm
  • The site is available through Class Notes
  • All course related material will be posted on
    this site
  • Lectures will be placed on the site before class
  • Check the site often

4
Class Notifications
  • Make sure to check the following website for
    class notices
  • http//www.uwindsor.ca/courses/notices

5
Course Outline Highlights
  • See the course outline for a full review of the
    following information
  • Course Description/Objectives
  • An introduction to basic concepts of
    psychological testing, with a focus on test
    development, measurement, and test evaluation.
    Properties of good test items and scales, such as
    reliability and validity, will be analyzed.
    Standard tests used to assess personality,
    achievement, and aptitudes will be surveyed.
    (Prerequisite 02-250.)

6
Course Requirements
  • Required Textbook
  • Kaplan, R. M., Saccuzzo, D. P. (2005).
    Psychological Testing Principles, Applications,
    and Issues, 6th Edition. Toronto Wadsworth.
  • Evaluation
  • 1 Midterm Exam (June 5) 30
  • Assignment (due June 21) 30
  • Final Exam (June 26, 700 PM) 40

7
Course Outline Highlights
  • Midterm and Final Examinations
  • ONE MID-TERM EXAM
  • Monday June 5th (Chapters 1-10 18 pages
    512-525 )
  • FINAL EXAMINATION
  • Monday June 26th from 700 P.M. to 1000 P.M.
    (Chapters 11-21 not 18 or 20 )
  • Both exams will cover assigned textbook readings
    and in-class material
  • The final exam is NOT cumulative

8
Course Outline Highlights
  • All exams are closed-book format. You may NOT
    bring any material (e.g., lectures notes or the
    class textbook) to any exam. The exams will
    include (but are not limited to) multiple choice
    questions, fill-in-the blank, definitions, short
    answer questions, or essays. Further details will
    be provided in class.
  • You should bring pens and pencils to both the
    Midterm and Final exams. You must bring your
    University of Windsor student ID Card to both
    exams.

9
Course Outline Highlights
  • Missed Tests You must take the midterm and final
    exams during the scheduled times
  • Acceptable reasons
  • Medical/family emergency or extreme circumstances
  • Supporting documents (e.g., physicians note)
    must be submitted to the instructor within one
    week following the missed test
  • Unacceptable reasons
  • Travel, special occasions, conflicts with other
    courses, or job-related scheduling conflicts
  • You will receive a grade of zero for these
    reasons or if supporting documents are not
    provided

10
Course Outline Highlights
  • Note The final exam cannot be re-written at
    another time
  • If it is missed for a valid reason, the student
    must apply for aegrotat standing through the
    Registrars Office

11
Course Outline Highlights
  • The University Calendar explains the regulations
    regarding plagiarism and other academic
    dishonesty
  • It is your responsibility to familiarize yourself
    with these regulations

12
Course Outline Highlights
  • Assignment
  • Due AT THE BEGINNING OF CLASS on Wednesday June
    21st
  • Assignments received after 630 P.M. SHARP on the
    due date without an acceptable, documented reason
    will be subject to a 5 grade penalty per day
    late (including weekend days)
  • Details will be provided soon
  • Worth 30 of final grade

13
Course Outline Highlights
  • You may earn up to two bonus points in this class
  • You can earn these in two ways
  • Participation in research
  • Completion of a bonus assignment posted online
    mid-June

14
Sign Up for Participant Pool!!
  • Earn up to 2 bonus points
  • Sign up on the web (takes less than 5 minutes)
  • http//uwindsor.experimentrak.net/
  • Or access through Psych homepage
  • You MUST sign up by midnight May 21st to be
    included (no exceptions)

15
Course Outline Highlights
  • Important Dates
  • May 19 Last day to register for class
  • May 21 Last day to sign up for Participant Pool
  • June 5 Midterm Exam (in class)
  • June 9 Last day to drop class (you will
    automatically receive a final grade after this
    date)
  • June 21
  • Assignment due at the beginning of class
  • Course Evals completed in class
  • Last lecture
  • June 26 700 - 1000 P.M. Final Exam

16
Introduction and Definitions
  • Test
  • Psychological Test
  • Scales
  • State vs Trait
  • Administration Individual vs Group
  • Test Battery
  • Standardization Sample
  • Standard Conditions
  • Representative Sample

17
More Testing
  • Measuring Human Ability
  • Achievement
  • Aptitude
  • Intelligence
  • Measuring Personality
  • Structured
  • Projective
  • Psychological Testing

18
Stats Review Descriptive/Inferential Statistics
  • Descriptive Statistics techniques for
    organizing, summarizing, representing and
    extracting information from numerical data
  • These are used to describe data (e.g., Mean,
    Standard Deviation)
  • Inferential Statistics rules and procedures for
    inferring the characteristics of populations from
    sample data (inferring parameters from
    statistics)
  • These are used to make inferences about a
    population (e.g., Correlation)

19
Types of Measurement
  • There are 4 types of measurement most often used
    in statistics
  • Nominal (categories)
  • Ordinal (rank order)
  • Interval (no absolute zero)
  • Ratio (absolute zero)
  • They differ on magnitude, equal intervals, and
    absolute zero

20
Organizing Data
  • Frequency Distributions A frequency distribution
    is a table which shows the number of individuals
    or events that occurred at each measurement value
  • Table/Histogram

21
Example
  • Age Frequency
  • 18 14
  • 19 85
  • 20 58
  • 21 40
  • 22 35
  • 23 16
  • 24 10
  • 25 6
  • 26 4

22
Percentile Rank (Pr)
  • Steps
  • Determine how many cases fall below X (B)
  • N
  • Divide cases below (B) by N
  • Multiply by 100
  • Pr (B/N)100

23
Mean
  • The mean of a sample of X scores is symbolized as
    ? , which is said as X bar
  • The mean of a population of X scores is
    symbolized by the Greek letter mu (µ)

24
Standard Deviation
  • The square root of the average deviation from the
    mean

25
Standard Deviation
  • Variability The extent numbers in a data set are
    dissimilar (different) from each other
  • The larger the standard deviation, the larger the
    variability in the data
  • Standard deviation expresses variability in the
    same units as the data
  • The standard deviation of a sample of X scores is
    symbolized as s
  • The standard deviation of a population of X
    scores is symbolized by the Greek letter sigma

26
Z-scores
  • Z-Scores (or standard scores) are a way of
    expressing a raw scores place in a distribution
  • Z-score formula

27
Z-scores
  • A z-score is a better indicator of where your
    score falls in a distribution than a raw score
  • A student could get a 75/100 on a test (75) and
    consider this to be a very high score

28
Z-scores
  • If the average of the class marks is 89 and the
    (population) standard deviation is 5.2, then the
    z-score for a mark of 75 would be
  • 89 5.2
  • z (75-89)/5.2
  • z (-14)/5.2
  • z -2.69

29
Z-scores
  • This means that a mark of 75 is actually 2.69
    standard deviations BELOW the mean
  • The student would have done poorly on this test,
    as compared to the rest of the class

30
Z-scores
  • z 0 represents the mean score (which would be
    89 in this example)
  • z lt 0 represents a score less than the mean
    (which would be less than 89)
  • z gt 0 represents a score greater than the mean
    (which would be greater than 89)

31
Z-scores
  • A z-score expresses the position of the raw score
    above or below the mean in standard deviation
    sized units
  • E.g.,
  • z 1.50 means that the raw score is 1 and
    one-half standard deviations above the mean
  • z -2.00 means that the raw score is 2 standard
    deviations below the mean

32
Properties of Area Under the Normal Distribution
.3413
.3413
.1359
.1359
.0215
.0215
.0013
.0013
z -3 -2 -1 0
1 2 3
33
Areas of Normal Distribution
  • Appendix I, Part II (p. 635)
  • Lets say we want to know the area between the
    mean and z 0.20
  • Look under z 0.200 (row .2, column .00)
  • The proportion 0.0793
  • Therefore, .0793 (or almost 8) is the proportion
    of data scores between the mean and the score
    that has a z score of 0.20

34
Example cont.
  • This means that the area between the mean (z
    0.00) and z 0.20 has an area under the curve of
    0.0793

.0793
.4207
z 0 0.20
35
Example cont.
  • Since the normal curve is symmetrical, the area
    between the mean and z -.20 is equal to the
    area between the mean and z .20

.0793
.0793
.4207
.4207
Z -0.20 0 0.20
36
But Why Know This?
  • Z-scores and percentile
  • The percentile for a z-score of 0.20 is as
    follows (remember distribution symmetry)
  • .5000 .0793
  • .5793
  • Multiply by 100 57.93 percentile
  • Note Percentiles and Percentile Rank are not the
    same thing

37
McCalls T
  • Transforms raw scores to a distribution with mean
    50, s 10
  • Standard scores, not normalized score

38
Quartiles and Deciles
  • Quartile percentage scale divided into 4 groups
  • Q1 25th percentile
  • Q2 median or 50th percentile. Etc
  • Interquartile range middle 50 of distribution
  • Decile percentage scale divided into 10 groups
  • D1 10th percentile

39
Stanine
  • Transforms raw scores to standard nine scores
  • 1 to 9, mean 5, s 2
  • Convert data to z-scores
  • Convert z-scores to percentiles (Appendix 1)
  • Use table to convert to stanines

40
Norms
  • Based on distribution of sample scores
  • Used to understand raw scores (norm-referenced
    test)
  • Remember representative sample
  • Age-related norms
  • Tracking
  • Gender norms

41
Criterion-Referenced Tests
  • Comparison of test performance with a specified
    set of criterion skills
  • Mastery of material

42
Correlation
  • We are often interested in knowing about the
    relationship between two variables
  • We are asking whether one variable (X) is related
    to another variable (Y). Stated differently Are
    X and Y correlated?
  • More specifically Are changes in one variable
    reliably accompanied by changes in the other?
  • Correlation coefficients

43
Graphing Relationships
  • When height and weight scores are plotted, we see
    some irregularity.
  • We can draw a straight line through these points
    to summarize the relationship.
  • The line provides an average statement about
    change in one variable associated with changes in
    the other variable.

r .77
44
Correlation
WEIGHT
HEIGHT
45
Degrees of linear correlation
46
Degrees of linear correlation
47
Characteristics of r
  • r has two components
  • The degree (magnitude) of relationship
  • The direction of relationship
  • r ranges from 1.00 to 1.00
Write a Comment
User Comments (0)
About PowerShow.com