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Measurement, Evaluation, Assessment and Statistics

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Presentation on theme: "Measurement, Evaluation, Assessment and Statistics"— Presentation transcript:

1 Measurement, Evaluation, Assessment and Statistics

2 Test and Measurement The heart of kinesiology. Why?
Test – tool or instrument used to make a measurement. Measurement – score on a test. Quantitative and assigns a number to a performance. (qualitative?)

3 Evaluation and Assessment
Eval – interpretation of the measurement. Gives it meaning. Prescribe – correct any deficits. Assessment – the process of measure, eval, identify and prescribe. Skills or health related measures.

4 WHY?

5 Reasons for Measurement and Evaluation
Motivation Study material Practice skills Prepare for post-test Diagnosis Assess strengths and weaknesses Determine baseline Skills vs fitness levels Prescription

6 Assignment?

7 Reasons for Measurement and Evaluation cont…
Classification Group students Homogeneous vs heterogeneous Control intensity of exercise or knowledge Achievement Progression of objectives and student Effectiveness of program Determine grades Subjective vs objective

8 Achievement?

9 Reasons for Measurement and Evaluation cont…
Instruction and program Compare two groups or methods Prediction Future performance Research (systematic in-depth analysis of a question) Determine grades Subjective vs objective

10 Objective vs Subjective?

11 Objective vs Subjective?

12 Statistics Organization and analysis of numerical data.
Simple arithmetic and algebra. Must follow the steps. Add, subtract, multiply and divide.

13 Statistics cont… Analyze and interpret data Understand research
Provides meaningful evaluation Interprets scores relative to one another Understand research Professional journals Practice their conclusions Essential for your continued growth in the field Do not believe everything you read.

14 Statistics cont… Standardize scores Determine worth of a test
Units differ among tests Standardization allows comparison (SAT) Determine worth of a test Validity and reliability Continuum Consider the appropriateness of a test

15 Appropriateness?

16 Appropriateness?

17 Distribution of Scores

18 Descriptive Stats Data – result of the test or the scores.
Variable – dependent characteristic or what you are measuring. Population – all subjects. Sample – subgroup of the total population. Random sample – everyone has an equal opportunity to be included.

19 Descriptive Stats cont…
Statistic – values from a sample. Descriptive – stats describe the sub-group only. Inferential – projections to a larger population. Discrete – whole numbers only. Continuous– broken down by decimal place.

20 Scales Nominal – code scoring with no quality comparison between groups. Ordinal – rank scoring from highest to lowest with no comparison of scores. Interval – no absolute zero but distance between scores is measured. Ratio – absolute zero and measured distance between scores.

21 Normal Distribution

22 Distribution cont… Bell shape – symmetrical and mirrored with mean, median and mode all same. NEVER OCCURS!! Skewed – tail determines the skew because mean is pulled. Bimodal – two high points.

23 Rank

24 Measures of Central Tendency

25 Fundamental Measures Maximum and minimum Range Sum N

26 Data Set

27 Mean Arithmetic average Sum divided by the number of scores
Most sensitive Considers all information Pulled away by extreme scores (outliers) Two decimal places

28 Data Set

29 Median Exact middle of scores. 50th percentile
Not affected by outliers Position only Not used for stats Find half of N Odd scores will be middle Even will be average of two middle

30 Data Set

31 Mode Score that occurs most frequently May be bimodal
May have no mode at all Least used stat Not affected by extreme scores

32 Data Set

33 Quartiles Divide scores into 4 equal parts Multiply N by .75 or .25
Find score or average two scores

34 Data Set

35 Central Tendency

36 Normal Bell Curve?

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