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EXSS 254 Final
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Terms in this set (72)
Characteristics of a normal distribution
Bell-shaped curve, symmetrical distribution about vertical axis of the curve (mirrored), greatest number of scores in middle of curve, and all measures of central tendency are at the vertical axis
Leptokurtic
Groups of individuals who are very similar in ability and curve is pointed, homogeneous
Platykurtic
If group consists of individuals with a wide range of ability, curve is flat, heterogeneous
Bimodal
Group of scores has two modes, the curve has two high points
Skewed
A curve with scores clustered at one end
Mean
Most generally used measure of central tendency, arithmetic average of distribution of scores
Mean is calculated by
Summing all the scores and dividing by total number of scores
Most sensitive of all measures of central tendency
Mean
Most appropriate measure of central tendency to use for ratio data and may be used on interval data
Mean
Considers all information about the data and is used to perform other important statistical calculations
Mean
Influenced by extreme scores
Mean
Mean
The sum of
Individual Score
X
The total number of scores in a distribution
N
Formula for calculating mean
Median
The score that represents the exact middle in the distribution, 50th percentile
Not affected by extreme scores
Median
Is a measure of position
Median
Not used for additional statistical calculations
Median
Steps for calculation of median
1. Arrange scores in ascending/descending order
2. Multiply N by 0.50 to find 50% distribution
3. If number of scores is odd, P50 is middle score
4. If number of scores is even, P50 is average of two middle scores
Mode
Score that occurs most frequently
The least used measure of central tendency
Mode
Not used for additional statistical calculations
Mode
Not affected by extreme scores, the total number of scores, or their distance from center of distribution
Mode
The mean, median, and mode are the same for..
Normal Distribution
The farther away from the mean and median the mode is, the less _____ the distribution
Normal
In a negatively skewed curve, the scores are clustered at the ____ end of the scale
Upper
In a positively skewed curve, the scores are clustered at the ____ end of the scale
Lower
Variability
The spread or scatter of scores; also known as dispersion or deviation
The measures of variability are..
Range, quartile deviation, and standard deviation
Range
Determined by subtracting the lowest score from the highest score
Dependent of two extreme scores
Range
Indicates nothing about the variability of the scores
Range
Least useful measure of variability
Range
Range formula
R= High score - Low score
R= Hx-Lx
Quartile Deviation
The spread of the middle 50% of the scores around the median
Uses the 75th percentile and 25th percentile to determine deviation
Quartile Deviation
Indicates amount that needs to bee added to and subtracted from the median to include middle 50%
Quartile Deviation
Usually is not used in additional statistical calculations
Quartile Deviation
Steps for calculating Q3
1. Arrange scores in ascending order
2. Multiply N by 0.75 to find 75% of distribution
3. Count up from the bottom score to the number determined in step 2.
Standard Deviation
Most useful and sophisticated measure of variability, describes the scatter of scores around the mean, more stable
It is the square root of the variance, which is average of the squared deviations from the mean
Standard Deviation
Is applicable to interval and ratio level data, includes all scores, and is most reliable measure of variability
Standard Deviation
Used with the median
Standard Deviation
A relatively small standard deviation indicates that the group being tested has little variability or much variability
Standard Deviation
Used to perform other statistical calculations
Standard Deviation
Standard Deviation symbol
s
Deviation score symbol
d
Individual score symbol
X
Standard deviation formula
Percentile
A point in the distribution of scores below which a given percentage of the scores fall
Percentile Rank
The percentage of the total scores that fall below the given score, indicates the position of a score in a distribution in percentage terms
Z-score
Represents the number of standard deviations by which a raw score deviates from the mean
T-score
Has a mean of 50 and a standard deviation of 10. May extend form 0 to 100 but is unlikely that it would fall below 20 or above 80
Correlation
A statistical technique used to express the relationship between two sets of scores
Linear Correlations
Degree to which a straight line best describes the relationship between two variables.
Correlation Coefficient
Number that represents the correlation
The values always range from +1.00 to -1.00
Correlation Coefficient
A positive coefficient indicates ____ relationship.
Direct
A negative coefficient indicates ____ relationship.
Inverse
A correlation of or very close to .00 indicates ___ relationship.
No
A correlation of or very close to 1.00 indicates ____ relationship
Strong
Scattergram
Graph used to illustrate the relationship between two variables
Preparing a scattergram
1. Determine range
2. Designate one variable as X and one as Y
3. Draw and label axes
4. Plot each pair of scores on the graph by placing a point at the intersection of the two scores
Statistical significance
Reliability
Null hypothesis
Predicts there will be a difference in the alternative hypothesis.
Degrees of Freedom
Concept is used in all statistical tests
Level of Significance
Probability of rejecting a null hypothesis when its true. Two most common levels are 0.05 and 0.1.
Standard Error of the Mean
Standard Error of the Mean..
The standard deviation of the sampling distribution
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