Statistics Exam Review
CHAPTER 1
Individuals are the objects described by a set of data. Individuals may be people, but they may also be animals or things.
A variable is any change of an individual. A variable can take different values for different individuals.
A categorical variable places an individual into one of several groups or categories.
A quantitative variable takes numerical values for which arithmetic operations such as adding and averaging make sense.
The distribution of a variable tells us what values the variable takes and how often it takes these values
A time plot of a variable plots each observation against the time at which it was measured. Always mark the time scale on the horizontal axis and the variable of interest on the vertical axis. If there are not too many points, connecting the points by lines helps show the pattern of changes over time.
Standard Deviation s – The variance s2 of a set of observations is the average of the squares of the deviations of the observations from their mean. In symbols, the variance of n observations X1, X2, …, Xn is
CLASS 1: Two basic types of data: 1) Quantitative – Response is a #; 2) Qualitative (categorical) – original question being asked is not a number, usually a word; “what % fell into each category.
Different types of quantitative data: 1. Ratio has a point of origin, like on the kelvin scale the 0 means a complete absence of the thing being measured. A ratio scale has a logical zero value. In measuring distance around the track, the starting line is a 0 point and half way around the mile-long outer track would be 2,640 feet. A horse that has run 100 yards has run twice far as a horse that has run 50 yards. One can say that the outer track is three times as long as the inner. 2. Ordinal – you can say this is higher than that one, can also be used to put people into groups 3. Interval scales measure distance but do not have a logical zero point that makes absolute magnitudes measurable; scale is consistent
Individuals are the objects described by a set of data. Individuals may be people, but they may also be animals or things.
A variable is any change of an individual. A variable can take different values for different individuals.
A categorical variable places an individual into one of several groups or categories.
A quantitative variable takes numerical values for which arithmetic operations such as adding and averaging make sense.
The distribution of a variable tells us what values the variable takes and how often it takes these values
A time plot of a variable plots each observation against the time at which it was measured. Always mark the time scale on the horizontal axis and the variable of interest on the vertical axis. If there are not too many points, connecting the points by lines helps show the pattern of changes over time.
Standard Deviation s – The variance s2 of a set of observations is the average of the squares of the deviations of the observations from their mean. In symbols, the variance of n observations X1, X2, …, Xn is
CLASS 1: Two basic types of data: 1) Quantitative – Response is a #; 2) Qualitative (categorical) – original question being asked is not a number, usually a word; “what % fell into each category.
Different types of quantitative data: 1. Ratio has a point of origin, like on the kelvin scale the 0 means a complete absence of the thing being measured. A ratio scale has a logical zero value. In measuring distance around the track, the starting line is a 0 point and half way around the mile-long outer track would be 2,640 feet. A horse that has run 100 yards has run twice far as a horse that has run 50 yards. One can say that the outer track is three times as long as the inner. 2. Ordinal – you can say this is higher than that one, can also be used to put people into groups 3. Interval scales measure distance but do not have a logical zero point that makes absolute magnitudes measurable; scale is consistent