Chapter 1-4 Flashcards
summation notation
The act of processing the sum
Deviation score
The difference between an observation or value x and the mean value.
Absolute deviation
The distance between each value in the data set and that data sets mean.
Prediction vs criterion
The main difference between a criterion variable and a predictor variable is that a predictor variable is used to find the values of the criterion variable.
Frequency distribution.
The pairing of the value of the variable with their associated frequencies.
Histogram
The graphical representation of a frequency distribution.
Symmetry
Where both sides of the frequency distribution are the same. Have a middle point that split both sides.
Skew
Skew is the tail length on either side of the frequency distribution.
Right skew
A tail that is longer on the right side.
Left skew
A tail that is longer on the left side.
Kurtosis
The shape of the distribution
Platykurtic
A relative flat histogram.
Leptokurtic
Skinny tails on both sides
Mesokurtic
Between both flat and skinny tails
Modality
Describes the number of peaks in a data set. Unimodal, bimodal, trimodal.
Central tendency
A summation that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution
Median
The value that cuts off the bottom 50% of the he score
Mean
The total of the scores divided by the number of scores
Deviation and distance
The distance and direction an individual value of x is from the mean of all the x’s.
ADD-absolute average deviation
Average distance scores are from the mean
Var- variance
The average squared distance scores are from the mean.
Standard deviation.
The square root of the average square scores are from the mean.
Range
The area of variation between upper and lower limits on a particular scale. Highest to lowest distance.
Location of CT vs spread
The mean can stay the same, as long as the spread is consistent.
Conditional distribution
It’s the distribution of one variable upon one level of another variable.
The more the difference, the bigger the correlation. Skews etc
The covariance
The value that one variable corresponde with another. When a value is the same as the mean it has zero covariance.
Pearson R
The linear correlation between two variables, measured on a scale of standard deviation.
Correlation coefficient
Index of linear and non linear only when it’s bounded. As in between -1 and 1.
Invariant
A function, quantity, property which remains unchanged when a specified transformation is applied.
Outliers
Any value that has a large influence on the value of a statistic calculated on a set of data. Careful with mean instead use median.
Parameter
A characteristic that describes the population, which will be the average.
