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| Datat that were produced in the past for some other purpose but may help answer a present question |
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| We observe indiviuals and measure variables of interest but do not attempt to influence the response. |
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| Deliberately do something to individuals in order to ovserver their responses |
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| THe ovjects described by a set of data. Individuals may be people , but they may also be animal or things |
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| Any charecteristic of an individual . A variable can take different values for different individuals. |
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| Places an individual into one of several groups or categories |
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| Takes numerical values for which arithmetic operations such as adding and averaging make sense. |
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| Of the variable tells us what values the variable takes and how often it takes these values |
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| The language of chance , which can be predictable with the use of many repeitions. |
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| Gives a quick shape of the distribution while including the actual numerial value in the graph. Do not work well for large data sets. |
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| breaks the range of values of a variable into classes and displays only the count or percnet of the observations. |
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| Where the tail of one side is much longer then the tail of another side thus skewing the data. |
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| Plots each ovservation against the time at which it was measured.Alpways put time on the horizontal scale of your plot and the variable you are measuring on the vertical scale. |
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| Look for shape, center , and spread(skewed or symmetric). |
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| Observations that lie outside the overall pattern of a distrbution. |
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Arrange the observations in increasing order and locate the median M in the order list of ovservations.
2. The first quartile is the median of the observation whose position in the ordered list is to the left of the lovation of the overvall mean.
3. Do same thing for the right side. |
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A set of observations consists of the smallest observation, the first quartile, the median , the third quartile, and the largest observation , written in order from smallest ot largest.
Summary is:
Minumum, Q1,Median, Q3,Maximum |
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| A graph of the five number summary |
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| Use the interquartile RAnge which is q3-q1. Then you multiply that by 1.5 and then add that to Q3 or subtract it from Q1 |
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VAriance squared. Standard deviation measures the spread of the data from the mean.
Properties: s measures about the mean and should be used only when the mea is chosen as the measure of center
S=0 only when there is no spread/variablity . THis happens only when all observations have the same value. Otehrwise s>0. AS the observations become mroe spread out about their mean s gets larger.
s, like the mean x bar, is not resistant. A few outliers can make s very large. |
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| changes the orignal variable x into the new variable x new given by an equation of the form. pg 90 When you add a constant to all values in a data set , the mean and medain increase by that constant.When you mutiply by a constant then the mean, median, IQR, and standard deviation are muplied by the constant. |
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converting scores from origanal values to standard deviation units
z=(x-mean)/standard deviation |
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Always on or above the horizontal axis and has area exactly 1 undereath it.
A denisty curve describes the overall pattern of a distribution . The area under the curve and above any interval of values on the horizontal axis is the proporiton of all ovservations that fall to that interval.
Median of a Density Curve= equal areas point , the point that divides the area under the curve in half.
Mean of a density curve=balanace point at which the curve would balance if made of solid material. |
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When a density curves are symmetric, single peaked , and bell shaped.
Described using the 68-95-99.7
68- between one standard deviation of the mean
95-all data falls between 2standard deviation of the mean
99.7 - all the data falls betweeen 3 standard deviation of the mean |
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| Normaly Probablility plot |
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| If the points on a Normal Probality plot lie close to a straight line, the plot indicates that the data are Normal systematic deviations from a stragiht line indicate a non-Normal distribution. Outliers appear as points that are far away from the overall pattern of the plot. |
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| Measure an outcome of a study |
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| Explains or influences change in a response variable. |
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| Shows the relationsip between two quantittavie variables measured on teh same individuals . Teh values of one variable appear on the hoirzontal axis and the values of the other variable appear on the vertical axis . Each individual in the data appears as teh point in the plot fixed by the values of both variables for that individual. |
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| Interpreting a Scatterplot |
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| In any graph of data, look for the overall pattern and for striking deviations from that pattern. You can describe the overall pattern of a scatterplot by teh direction , form and strength of the relationship . An important kind of deviation is an outlier , an invididual value that falls outside the overall pattern of the relationship. |
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| Measures teh direction and strength of the linear relationship between two quantitative variables. Correlation is usually written as r. |
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