Lecture 5 - Introduction to Statistics

Question 1

Measures of Central Tendency

Answer 1

Any descriptive summary statistic that identifies the ‘middle point’ or typical value in a distribution of scores; there are three types: mean, median, and mode.

Question 2

Mean

Answer 2

A measure of central tendency calculated by dividing the sum of a set of numbers by the number of terms.

The mean is sensitive to outliers, and therefore may be less useful in the presence of a skewed distribution.

Question 3

Median

Answer 3

A measure of central tendency calculated by arranging a set of numbers in numerical order and locating the middle term.

The process is simple with an odd number of terms, but with an even number of terms, there will be two middle values culled out from a set of numbers. Average the two values and you have the median of an even number of terms.

Question 4

Mode

Answer 4

A measure of central tendency that concerns itself with the most frequent values in a set of data.

If there is a mode within a set of data, it can be bimodal or multimodal.

Most commonly used in ordinal and nominal data sets.

Question 5

Measures of Dispersion

Answer 5

Any descriptive statistic that identifies the spread of a set of continuous data; there are five types: range, minima, maxima, variance, and standard deviation.

Question 6

Range

Answer 6

A measure of dispersion calculated by identifying the minima and maxima, finding their difference, and adding 1.

A crude measure used to provide basic details about data by showing how widely spread the extremes are.

Question 7

Minima and Maxima

Answer 7

Measures of dispersion identifying the lowest and highest values in a data set, respectively.

Question 8

Variance (s²)

Answer 8

A measure of dispersion calculated by finding the mean in a set of data, evaluating each participant’s deviance from the mean (the difference of individual score and mean), squaring the deviations, adding the squared deviations, and dividing by the number of participants minus one.

Variance reveals the average degree of deviation of a set of values in a distribution from the mean of those values.

Question 9

Standard Deviation

Answer 9

A measure of dispersion calculated by finding the degree of variance and then it’s square root.

The standard deviation reveals the same general information as does the variance, but it remains in the same scale of units as the mean.

Question 10

Distributions of Data

Answer 10

Any descriptive statistical model that reveals all possible values of data and how often they occur.

Question 11

Normal Distribution

Answer 11

Otherwise known as the bell curve, it is a distribution of data regarded as ‘normal’. In such a theoretical distribution, the mean, median, and mode are equal and the majority of individuals cluster near this middle point with very few outliers at the extremes.

Question 12

Kurtosis

Answer 12

A distribution of data that displays the concentration of values about the mean represented by how tall or how flat the distribution is.

This reveals how thin or broad a distribution is. it also says something about the value of scores - more thin distributions might indicate a surge of positive scores, and more broad distributions could indicate wider range of less positive scores.

Platykurtic distributions refer to those that are flat and short; leptokurtic refers to those that are thin and tall.

Question 13

Skew

Answer 13

A distribution of data in which the distribution is not symmetrical around the mean.

Reveals an asymmetry amongst scores.