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Psychological testing-Norms. M. A. Part I Semester I By Balaji Niwlikar. Basic Statistical Concepts:. Measures of Central tendencies: Mean Average Median Middle value Mode Most repeated score Measures of Variability: Standard deviation Quartile deviation Range Z Scores. Norms.
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Psychological testing-Norms M. A. Part I Semester I By BalajiNiwlikar https://www.careershodh.com/
Basic Statistical Concepts: • Measures of Central tendencies: • Mean • Average • Median • Middle value • Mode • Most repeated score • Measures of Variability: • Standard deviation • Quartile deviation • Range • Z Scores https://www.careershodh.com/
Norms • Standard/Average performance . • Methodology – to understand psy tests and proper interpretation of scores. • Norms, Reliability , Validity, Item Analysis and Test Design. • Raw Scores - 35 in English. 20 in math ???? • Expressed in different units –kg, hour , no .of correct/incorrect responses, no. of trails, • So we cant just directly compare it. • It can only interpreted in clearly defined and uniform frame of references . https://www.careershodh.com/
Norms • Definition: “Norms may be defined as the average performance on a particular test made by a standardization sample.” Standardization sample-true representation population, cross cultural, • Empirically established . • To discover where S/he falls in that situation - we convert Raw scores into Derived Score- • Derived Score- • Difficultylevel – all score low 1,5,10 /1000. we can compare D scores • 2 objectives /purpose/ goals of Derived Score . • To indicate the individual’s relative standing in the normative sample and thus permit an evaluation of her/his performance in reference to other persons. • To provide comparable measures that permits a direct comparison of the individuals performance on different tests. https://www.careershodh.com/
Norms • Types if evaluation • Formative /concurrent Evaluation • To evaluate learning • Not standard and Informal way • Summative Evaluation • To find out which area is strong / weak • Useful in Training program, language ,math • Diagnostic Evaluation • At end of program • Follow up Evaluation • In Corporate areas • Attitude changing Program https://www.careershodh.com/
Norms • Steps in developing Norms: • Defining the target population • Normative group -based on intention of test . • Selecting the sample from the target population • True representative sample. • Cross sectional • Large sample • Random sampling • Standardizing the conditions • Test administration must be standard, valid https://www.careershodh.com/
Types of Norms: • Derived Score- • Expressed in two major ways i.e types 1st Developmental Level Attended or 2nd relative position within a specific group https://www.careershodh.com/
Types of Norms: https://www.careershodh.com/
Developmental Norms • A way to attach meaning to scores. • To indicate how far an individual has progressed the normal developmental path. • Ex – children smile after certain age. • Binet proposed early developmental age norms and gave concept of Mental Age • Mental Age- • Binet –Simon • Items passed by the majority of 8 years old in standardised sample were grouped together and placed in the 8 year level. = Mental Age of 8. • 8 year old Sheldon Cupper scored well on intelligence test of 80 year old –means he has Mental Age of 80 year old https://www.careershodh.com/
Developmental Norms • Age equivalent norms: • Criteria – Ave. performance of standard sample at certain age level. • Most suitable for trait or ability which increases systematically. • e.g. Height, weight, Cog. Abilities, intelligence etc. • Limitations – • It is not fully standard and uniform unit for measurement for over all period. • Some of the traits can not be explained by age norms though they are related to age. Ex- maze learning will not develop after adolescent, IQ will not increased after 16 but vocabulary can. https://www.careershodh.com/
Developmental Norms • Grade Equivalent norms • Like age equivalent norms – criterion –Grade/Standard • In field of educations . Achievement test & educational test. • Ex -4th grade performance in math ,language skill. • The average no. of problems solved correctly on a math test by the 4th Grader in a standardization sample is 23,them raw score of 23 corresponds to grade equivalent of 4 • It can be expressed in decimal (4.5); If we considered months . • Limitations – • Same students in different subjects not comparables (math with social sciences). • Not suitable for higher grades level ( 1 subject for 2 years) • Not suitable for subjects which occurs rapidly growth in lower grades ;will be same in higher grade https://www.careershodh.com/
Developmental Norms • Ordinal scales – • Not like statistics (providing rank order to individual without knowledge about amount of differences between them ) • Designed to identify the stage reached by the child in the development of specific behavior functions • Originated from research of child psychology • Based on Model of Guttman Scale or simplex(1944)- successful performance at one level implies success at all lower level. • Success in functions of locomotion , concept formation, etc. • Gesell Developmental Schedule (1947)–child has attained a certain level in –motor, adaptive ,language ,& personal-social. • Development theory of Piaget – schema ,object permanence https://www.careershodh.com/
Within-Group Norms • Almost all psychological test provides it. • Used most near comparable standard group ex - same chronological age /same school grade. • Within group scores / norms have uniform and clearly defined quantitative meaning . • Used in most of statistical analysis. https://www.careershodh.com/
four levels or scales of measurement. (noir) • Nominal scales – • involve classification or categorization based on one or more distinguishing characteristics, • Ex - “men,” “1,” “B,” or “women,” “2,” or “A.” • Ordinal scales- • permit classification and rank ordering on some characteristic • Ex- merit list of SP College. • Interval scales - • contain equal intervals between numbers. • But like ordinal scales, interval scales contain no absolute zero point • Ex -IQs of 80 and 100 • Ratio Scales • In addition to all the properties of nominal, ordinal, and interval measurement, • It scale has a true zero point. https://www.careershodh.com/
Within-Group Norms • Percentiles: • Most common and popular • Percentile -% of persons (standard sample) fall below a given point. • Percentile and Percentile Rank are two different concepts. • ex – if the 30% of the person obtain fewer than 18 problems correct on math then raw score of 18 corresponds to 30th percentile (P30) i.e. percentile rank is 30 and percentile score is 18 • Lower the percentile the poorer the persons standing. • PR 50 –median .PR 25 and PR 75 are called 1st n 3rd quartile points .. • Different from percentage ( %) – raw score where percentile is derived score. • PR 0 & PR 100? • a raw score lower/more than obtained in in the standard sample. https://www.careershodh.com/
Percentiles: • Simple to understand. • Familiar to population. • simple for computation. • Percentiles are placed on an Ordinal Scale means it regarded as rank in group of 100 • Limitation – inequality of unites • The distance between the extreme PRs is larger than the PRs in the middle of the NDC. • Percentiles can be converted into large number of other norms. https://www.careershodh.com/
Percentile https://www.careershodh.com/
Within-Group Norms: • Standard scores : • Increasing trend . most satisfactory derived score. • a SS is a raw score that has been converted from one scale to another scale, where the latter scale has some arbitrarily set Mean and SD. • Raw scores may be converted to standard scores to easily interpret. • With a standard score, the position of a test taker’s performance relative to other test takers is readily apparent. • SS can obtained by Linearly & Non linearly transformed • Ex -z scores, T scores, stanines, and some other standard scores. https://www.careershodh.com/
Standard scores : • Linearly transformed score – • They retain exact numerical relation of the original raw score. • Standard score duplicate all the properties of raw score thus all results are distortion less . • Units of the scale are equal so that they convey the same meaning throughout the whole range of the scale. • They removes the problem of inequality. • Simply known z scores https://www.careershodh.com/
Linearly transformed standard score • Standard score/ z scores – • It express the persons distance from the mean in the terms of SD of the distribution. • zero plus or minus one scale. This is so because it has a mean set at 0 and a SD set at 1. • z=(X-M)/SD Limitation of Linearly transformed standard score If one distribution is skewed and other is normally distributed then two standard scores cant be compared Lay people may uncomfortable with z-scores. • don't like negative numbers • uncomfortable with a z-score of 0 being average. • Ex- Swapnil got z-score of 0. https://www.careershodh.com/
Non Linearly transformed score • Non Linearly transformed score – • when the data under consideration are not normally distributed yet need compare with normal distributions . • Here ,the resulting SS does not necessarily have a direct numerical relationship to the original, raw score. • Examples • mental age, • percentile score, • Normalized standard score https://www.careershodh.com/
Non Linearly transformed score • Normalized standard score • SS which are expressed in the terms of normal distribution • Maeshall & Hales (1972) ‘’Normalized standard score which have been adjusted to produce a normal frequency distribution and convert to a standard base with pre assign Mean & SD’’. • NSS can expressed in same form of linearly transformed SS i.e. with Mean= 0 and SD =1. • Examples • T scores ,stanines, sten ,C scores , Deviation IQ https://www.careershodh.com/
Normalized standard score • T Scores • called a fifty plus or minus ten scale; i.e, a scale with a mean set at 50 and a standard deviation set at 10. • Devised by W. A. McCall (1922, 1939) and named a T score in honor of his professor E. L. Thorndike, • This system is composed of a scale that ranges from 5 SD below the mean to 5 SD above the mean. • T score = 50+/-10z https://www.careershodh.com/
Normalized standard score Stenines= 5+1.96Zn • Stanines • Standard nine. • Distribute entire scores into 9 units • It has mean @ 5 and SD at 1.96 • If researcher knows PR scores corresponding Stanines value can be calculated. • Stanines= 5+1.96 Zn • Zn –Normalized z scores (we already calculated PR.) • +v –reasonably easy to understand . • Useful to counselor, educational psychologist , selection & recruitment process.ad https://www.careershodh.com/
stanine https://www.careershodh.com/
Normalized standard score • Sten scores: • They are also called as Standard Ten. • After proposing 16PF Raymond Cattle proposed the concept of Sten scores. • It distributes entire score range into 10 units. • It has mean of 5.5 and SD of 2. • If researcher knows PR scores corresponding Stanines value can be calculated. Sten scores= 5.5+2Zn https://www.careershodh.com/
Sten Scores https://www.careershodh.com/
Normalized standard score • C Scores • G.P. Guilford • 11 standard units • Ranger from 0 to 10 https://www.careershodh.com/
Normalized standard score • Deviation IQ • IQ • Not comparable for different age group IQ of 115 @ Age 10 and IQ of 125 @Age of 12 • Deviation IQ is a Normalized standard score has M=100 & SD 16 for Stanford Binet Scale • Deviation IQ is a Normalized standard score has M=100 & SD 15 for Wheschlers intelligence test . https://www.careershodh.com/
Relativity of Norms • The theory talks about how norms are interchangeable. • It refers to the concept that if researcher knows one type of norm he can predict about the other. e.g. If researcher knows about percentile score of a subject that score can be converted into a Stanine or Sten score. • But in the case of linear norms relativity experiences limitations. • For conversion of the score one should know the shape of the distribution too. https://www.careershodh.com/
Relativity of Norms • Three principle reasons of test score variation – • Content –verbal/ numerical /spatial • Scale unit-different SDs-16/15 • Standardization of samples- slow/Ave/better will matter • Normative Sample- large, representative, selective factors, defined population • National Anchor Norms –solution for the lack of comparability – equipercentile method –scores are considered equivalent when they have equal percentiles for different test . • Specific Norms –standardize test on more narrowly defined population( ex 1st FYBA students ) – local norms • Fixed reference group- college board SAT -1st • Item Response Theory- used for difficulty. To established uniform ‘sample free’ scale of measurement ie applicable to person/group https://www.careershodh.com/
Computers & Interpretation of Test Scores • Computers play an important role in generating data analysis. • It helps in conduction of experiments. • It influences the process of test construction. • Calculation of item total correlation, item analysis is possible with the help of computers. • It is useful in the method of factor analysis too. • Following calculations became popular as well as possible due to computers. https://www.careershodh.com/
Computers & Interpretation of Test Scores https://www.careershodh.com/
Computers & Interpretation of Test Scores • Computer scoring • Interactive computer system • System for Interactive Guideline Information (SIGI) • Major concern • To score comparability • Narration interpretation scoring https://www.careershodh.com/
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