Research Methods and Statistics (20) Statistics Applied in Research Studies on tests and Tests Development Flashcards

1
Q

statistics that indicates the average or midmost score between the extreme scores in a distribution

A

Measures of Central Tendency

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2
Q

Identify the most typical or representative of entire group

Measures of Central Location

A

Goal of Measures of Central Tendency

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3
Q

the average of all the raw scores
- Equal to the sum of the observations divided by the number of observations
- Interval and ratio data (when normal distribution)
- Point of least squares
- Balance point for the distribution
- susceptible to outliers

A

Mean

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4
Q

– the middle score of the distribution
- Ordinal, Interval, Ratio
- for extreme scores, use median
- Identical for sample and population
- Also used when there has an unknown or undetermined score
- Used in “open-ended” categories (e.g., 5 or more, more than 8, at least 10)
- For ordinal data
- if the distribution is skewed for ratio/interval data, use median

A

Median

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5
Q
  • most frequently occurring score in the distribution
  • Bimodal Distribution: if there are two scores that occur with highest frequency
  • Not commonly used
  • Useful in analyses of qualitative or verbal nature
  • For nominal scales, discrete variables
  • Value of the mode gives an indication of the shape of the distribution as well as a measure of central tendency
A

Mode

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6
Q

statistics that describe the amount of variation in a distribution
- gives idea of how well the measure of central tendency represent the data
- large spread of values means large differences between individual scores

A

Measures of Spread or Variability

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7
Q
  • equal to the difference between highest and the lowest score
  • Provides a quick but gross description of the spread of scores
  • When its value is based on extreme scores of the distribution, the resulting description of variation may be understated or overstated
A

Range

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8
Q

difference between Q1 and Q2

A

Interquartile Range

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9
Q

interquartile range divided by 2

A

Semi-Quartile Range

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10
Q
  • approximation of the average deviation around the mean
  • gives detail of how much above or below a score to the mean
  • equal to the square root of the average squared deviations about the mean
  • Equal to the square root of the variance
  • Distance from the mean
A

Standard Deviation

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11
Q
  • equal to the arithmetic mean of the squares of the differences between the scores in a distribution and their mean
  • average squared deviation around the mean
A

Variance

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12
Q

Measures of Location - not linearly transformable, converged at the middle and the outer ends show large interval

expressed in terms of the percentage of persons in the standardization sample who fall below a given score

  • indicates the individual’s relative position in the standardization sample
A

Percentile or Percentile Rank

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13
Q

Measures of Location -dividing points between the four quarters in the distribution

Specific point

A

Quartile

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14
Q

refers to an interval

A

Quarter

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15
Q

Measures of Location - divide into 10 equal parts
- a measure of the asymmetry of the probability distribution of a real-valued random about its mean

A

Decile/STEN

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16
Q

Correlation - - interval/ratio + interval/ratio

A

Pearson R

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17
Q

Correlation ordinal + ordinal

A

Spearman Rho

18
Q

Correlation artificial Dichotomous + interval/ratio

A

Biserial

19
Q

Correlation artificial Dichotomous + interval/ratio

A

Point Biserial

20
Q

Correlation - nominal (true dic) + nominal (true/artificial dic.)

A

Phi Coefficient

21
Q

Correlation - Art. Dichotomous + Art. Dichotomos

A

Tetrachoric

22
Q

Correlation - 3 or more ordinal/rank

A

Kendall’s

23
Q

Correlation -nominal + ordinal

A

Rank Biserial

24
Q

Differences - two separate groups, random assignment
- e.g., blood pressure of male and female grad students

A

T-test Independent

25
Q

Differences - one group, two scores
- e.g., blood pressure before and after the lecture of Grad students

A

T-Test Dependent

26
Q

Differences - 3 or more groups, tested once
- e.g., people in different socio-economic status and the differences of their salaries

A

One-Way ANOVA

27
Q

1 group, measured at least 3 times
- e.g., measuring the focus level of board reviewers during morning, afternoon, and night sessions of review

A

One-Way Repeated Measures

28
Q
  • 3 or more groups, tested for 2 variables
  • e.g., people in different socio-economic status and the differences of their salaries and their eating habits
A

Two-Way ANOVA

29
Q
  • used when you need to control for an additional variable which may be influencing the relationship between your independent and dependent variable
A

ANCOVA

30
Q
  • 2 or more groups, measured more than 3 times
  • e.g., Young Adults, Middle Adults, and Old Adults’ blood pressure is measured during breakfast, lunch, and dinner
A

ANOVA Mixed Design

31
Q

Non-Parametric Tests - t-test independent

A

Mann Whitney U Test and Wilcoxon Signed Rank Test

32
Q

Non-Parametric Tests - one-way/two-way ANOVA

A

Kruskal-Wallis H Test

33
Q

Non-Parametric Tests - ANOVA repeated measures

A

Friedman Test

34
Q

Non-Parametric Tests - for 2 groups of nominal data

A

Lambda

35
Q

Chi-Square - - used to measure differences and involves nominal data and only one variable with 2 or more categories

A

Goodness of Fit

36
Q

Chi-Square - used to measure correlation and involves nominal data and two variables with two or more categories

A

Test of Independence

37
Q

used when one wants to provide framework of prediction on the basis of one factor in order to predict the probable value of another factor

A

Regression

38
Q
  • Y = a + bX
  • Used to predict the unknown value of variable Y when value of variable X is known
A

Linear Regression of Y on X

39
Q
  • X = c + dY
  • Used to predict the unknown value of variable X using the known variable Y
A

Linear Regression of X on Y

40
Q

– dichotomy in which there are only fixed possible categories

A

True Dichotomy

41
Q

dichotomy in which there are other possibilities in a certain category

A

Artificial Dichotomy