Download presentation

Presentation is loading. Please wait.

Published byIsaac Kirkpatrick Modified over 3 years ago

1
Jamil A. Malik (PhD) National Institute of Psychology Quaid-e-Azam Univeristy

2
Categorical Binary variable: Only two categories Nominal variable: More than two categories Ordinal variable: Categories have a logical order Continuous (entities get a distinct score): Interval variable: Equal intervals on the variable represent equal differences Ratio variable: Ratios of scores on the scale must also make sense

3
correlational or cross-sectional research where we observe what naturally goes on in the world without directly interfering with it experimental research where we manipulate one variable to see its effect on another Tertium quid (confounding variables): A third person or thing of indeterminate character Causality and Statistics

4
Independent design Repeated measure design Systematic variation Unsystematic (Random) variation Randomization and counterbalancing

5
Frequency distributions (histogram) Normal distribution (1)Skew: lack of symmetry (1)Positive (2)Negative (2)Kurtosis: pointyness (1)Leptokurtic (2)Platykurtic In a normal distribution the values of skew and kurtosis are 0

6
The mode Most frequent The median The Middle The mean The average

7
Range Difference of Largest and smallest Interquartile range Range of middle 50% Not affected by extreme scores Frequency distribution as probability distribution Normal distribution (z-score) ±1.96 (2.5% of extreem scores in a distribution) ±2.58 (1% of extreem scores in a distribution) ±3.29 (0.1% extreem scores in a distribution) Null hypothesis Alternate hypothesis

9
Degree to which a statistical model represents the data Sample and population Real world models Statistical Models

10
The mean Standard deviation and standard error Confidence intervals

11
One- and two-tailed tests Type I and Type II errors Effect sizes (d, r, eta sq, odd ratios) r =.10 (small effect): In this case the effect explains 1% of the total variance. r =.30 (medium effect): The effect accounts for 9% of the total variance. r =.50 (large effect): The effect accounts for 25% of the variance. meta-analysis Statistical power

Similar presentations

OK

REVIEW OF BASIC STATISTICAL CONCEPTS Kerstin Palombaro PT, PhD, CAPS HSED 851 PRIVITERA CHAPTERS 1-4.

REVIEW OF BASIC STATISTICAL CONCEPTS Kerstin Palombaro PT, PhD, CAPS HSED 851 PRIVITERA CHAPTERS 1-4.

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Ppt on assembly line balancing Ppt on synthesis and degradation of purines and pyrimidines definition Ppt on holographic technology adopted Ppt on marketing plan Ppt on ways to improve communication skills Ppt on biography of william shakespeare Ppt on mars one hoax File type ppt on cybercrime articles Ppt on conventional energy sources Ppt on allotropes of carbon