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Enhancing Study Skills and Research Methods in Academic Contexts

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24 diapositives · 379 Views · Sep 13, 2014

This unit, led by Dr. James Betts, focuses on developing essential study skills and research methodologies. Participants will explore various measurement levels (discrete/continuous) and academic grading (A*-F) while understanding concepts like central tendency, statistical validity, and hypothesis testing concerning gender differences in isometric muscular contraction. The curriculum emphasizes analytical techniques, exploring validity types (e.g., predictive, construct), and the impact of reliability on research outcomes. By the end of the course, students will effectively navigate statistical tools and methodologies required for academic success.

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  1. Developing Study Skills and Research Methods Unit Code: HL20107 Unit Leader: Dr James Betts J.Betts@bath.ac.uk

  2. Level of Measurement? Discrete/Continuous? Academic Grade (A*-F) Tides (+/-1 m, etc.) Nationality Body Mass (kg) Social Class Date (DD/MM/YYYY) Colour (nm) Shoe Size Refresher Test

  3. Mode (i.e. most frequently occurring score) + Median (i.e. middle score/50th percentile) + Mean (i.e. arithmetic average) + Indicators of Central Tendency

  4. Normal Distribution

  5. Logical Statistical Validity Face Content Concurrent Consistency Objectivity Predictive Construct Reliability AKA Criterion

  6. Face Validity Infers that a test is valid by definition It is clear that the test measures what it is supposed to Logical Validity • Content Validity • Infers that the test measures all aspects contributing to the variable of interest

  7. Concurrent Validity Infers that the test produces similar results to a previously validated test Statistical Validity • Predictive Validity • Infers that the test provides a valid reflection of future performance using a similar test

  8. Construct Validity Infers not only that the test is measuring what it is supposed to, but also that it is capable of detecting what should exist, theoretically Therefore relates to hypothetical or intangible constructs Logical/Statistical Validity

  9. Maturation History Pre-testing Statistical Regression Instrumentation Selection Bias Experimental Mortality. Threats to Internal Validity

  10. Inadequate Description Biased Sampling Hawthorne Effect Demand Characteristics Operationalisation. Threats to External Validity

  11. Reliability Subject 1 60 ml.kg-1.min-1 60 ml.kg-1.min-1 60 ml.kg-1.min-1 Subject 2 55 ml.kg-1.min-1 55 ml.kg-1.min-1 55 ml.kg-1.min-1 Subject 3 70 ml.kg-1.min-1 70 ml.kg-1.min-1 70 ml.kg-1.min-1

  12. Reliability Subject 1 60 ml.kg-1.min-165 ml.kg-1.min-1 65 ml.kg-1.min-1 Subject 2 55 ml.kg-1.min-160 ml.kg-1.min-1 60 ml.kg-1.min-1 Subject 3 70 ml.kg-1.min-175 ml.kg-1.min-1 75 ml.kg-1.min-1

  13. Reliability Subject 1 60 ml.kg-1.min-172 ml.kg-1.min-1 57 ml.kg-1.min-1 Subject 2 55 ml.kg-1.min-161 ml.kg-1.min-1 52 ml.kg-1.min-1 Subject 3 70 ml.kg-1.min-140 ml.kg-1.min-1 84 ml.kg-1.min-1

  14. Relative Reliability Subject 1 60 ml.kg-1.min-1 63 ml.kg-1.min-1 57 ml.kg-1.min-1 Subject 2 55 ml.kg-1.min-1 56 ml.kg-1.min-1 48 ml.kg-1.min-1 Subject 3 70 ml.kg-1.min-1 65 ml.kg-1.min-1 66 ml.kg-1.min-1

  15. Intrarater reliability The consistency of a given observer or measurement tool on more than one occasion Rater Reliability • Interrater reliability • The consistency of a given measurement from more than one observer or measurement tool

  16. Is there any difference in the length of time that males and females can sustain an isometric muscular contraction? Example Hypotheses: Isometric Torque Alternative Hypothesis (HA) or experimental (HE) There is a significant difference in the DV between males and females. Null Hypothesis (H0) There is not a significant difference in the DV between males and females

  17. Is there any difference in the length of time that males and females can sustain an isometric muscular contraction? Example Hypotheses: Isometric Torque Alternative Hypothesis (HA) or experimental (HE) There is a significantlyhigher DV for males than for females. Null Hypothesis (H0) There is not a significantlyhigher DV for males than for females.

  18. Example Hypotheses: Isometric Torque • Is there any difference in the length of time that males and females can sustain an isometric muscular contraction? N♀ N♂ n♀ n♂ 16 17 18 19 20 Sustained Isometric Torque (seconds)

  19. Type 1 Errors Type 2 Errors Statistical Errors

  20. SPSS Outputs

  21. Example Hypotheses: Isometric Torque • Is there any difference in the length of time that males and females can sustain an isometric muscular contraction? t-test Mean A Mean B 16 17 18 19 20 Sustained Isometric Torque (seconds)

  22. Example Hypotheses: Isometric Torque • Is there any difference in the length of time that males and females can sustain an isometric muscular contraction? Mean A Mean B 16 17 18 19 20 Sustained Isometric Torque (seconds)

  23. SPSS Outputs

  24. So which stats test should you use? Q1. What is the LOM? Q2. Is the data ND? Q3. Is the data paired or independent?