Characteristics of Data (CVDOT)

CVDOT

many samples of data are large, so understanding them requires that we organize, summarize, and represent the data in a way that allows us to gain insight

Characteristics of Data
1. Center: A representative value that indicates where the middle of the data set is located.
2. Variation: A measure of the amount that the data values vary.
3. Distribution: The nature or shape of the spread of the data over the range of values (such as bell-shaped).
4. Outliers: Sample values that lie very far away from the vast majority of the other sample values.
5. Time: Any change in the characteristics of the data over time.



Frequency and Histogram

Histogram is een grafische weergave van een frequency distirbiutie

Assessing Normality: Normal Quantile Plot

Some really important methods presented in later chapters have a requirement that sample data must be from a population having a normal distribution. We can see that a histogram is often helpful in determining whether the normality requirement is satisfied. However, histograms are not very helpful with small data sets.

Criteria for Assessing Normality with a Normal Quantile Plot Normal Distribution: The population distribution is normal if the pattern of the points in the normal quantile plot is reasonably close to a straight line, and the points do not show some systematic pattern that is not a straight-line pattern.
Not a Normal Distribution: The population distribution is not normal if the normal quantile plot has either or both of these two conditions:
• The points do not lie reasonably close to a straight line.
• The points show some systematic pattern that is not a straight-line pattern.

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