1. STATISTICS
ELEMENTARY
MARIO F. TRIOLA
EIGHTH
EDITION

2. STATISTICS ELEMENTARY MARIO F. TRIOLA
Chapter Introduction to Statistics
MARIO F. TRIOLA
EIGHTH
EDITION

3. Introduction to Statistics
Chapter 1
Introduction to Statistics
1-1 Overview
1-2 The Nature of Data
1-3 Uses and Abuses of Statistics
1-4 Design of Experiments

4. Statistics Two Meanings Specific numbers 1-1 Overview
Method of analysis

5. Statistics Specific number
numerical measurement determined by a set of data
Example: Twenty-three percent of people polled believed that there are too many polls.

6. Statistics Method of analysis
a collection of methods for planning experiments, obtaining data, and then then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data
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7. Definitions Population
the complete collection of all elements (scores, people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied.

8. Definitions Census Sample
the collection of data from every element in a population
Sample
a subcollection of elements drawn from a population
Emphasize that a population is determined by the researcher, and a sample is a subcollection of that pre-determined group. For example, if I collect the ages from a section of elementary statistics students, that data would be a sample if I am interested in studying ages of all elementary statistics students. However, if I am studying only the ages of the specific section of elementary statistics, the data would be a population.

9. The Nature of Data

10. Definitions Parameter
a numerical measurement describing some characteristic of a population
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11. Definitions Parameter population parameter
a numerical measurement describing some characteristic of a population
population
parameter

12. Definitions Statistic
a numerical measurement describing some characteristic of a sample

13. Definitions Statistic sample statistic
a numerical measurement describing some characteristic of a sample
sample
statistic

14. Definitions Quantitative data
numbers representing counts or measurements
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15. Definitions Quantitative data
numbers representing counts or measurements
Qualitative (or categorical or attribute) data
can be separated into different categories that are distinguished by some nonnumeric characteristics

16. Definitions
Quantitative data
the incomes of college graduates

17. Definitions Quantitative data
the incomes of college graduates
Qualitative (or categorical or attribute) data
the genders (male/female) of college graduates

18. Definitions
Discrete
data result when the number of possible values is either a finite number or a ‘countable’ number of possible values
0, 1, 2, 3, . . .

19. Definitions Discrete Continuous
data result when the number of possible values is either a finite number or a ‘countable’ number of possible values
0, 1, 2, 3, . . .
Continuous
(numerical) data result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps
Understanding the difference between discrete versus continuous data will be important in Chapters 4 and 5.
When measuring data that is continuous, the result will be only as precise as the measuring device being used to measure. 2 3

20. Definitions
Discrete
The number of eggs that hens lay; for example, 3 eggs a day.

21. Definitions
Discrete
The number of eggs that hens lay; for example, 3 eggs a day.
Continuous
The amounts of milk that cows produce; for example, gallons a day.

22. Definitions nominal level of measurement
characterized by data that consist of names, labels, or categories only. The data cannot be arranged in an ordering scheme (such as low to high)
Example: survey responses yes, no, undecided
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23. Definitions ordinal level of measurement
involves data that may be arranged in some order, but differences between data values either cannot be determined or are meaningless
Example: Course grades A, B, C, D, or F
Understanding the differences between the levels of data will help students later in determining what type of statistical tests to use.
Nominal and ordinal data should not be used for calculations (even when assigned ‘numbers’ for computerization) as differences and magnitudes of differences are meaningless.

24. Definitions interval level of measurement
like the ordinal level, with the additional property that the difference between any two data values is meaningful. However, there is no natural zero starting point (where none of the quantity is present)
Example: Years 1000, 2000, 1776, and 1492
Students usually have some difficulty understanding the difference between interval and ratio data. Fortunately, interval data occurs in very few instances.

25. Definitions ratio level of measurement
the interval level modified to include the natural zero starting point (where zero indicates that none of the quantity is present). For values at this level, differences and ratios are meaningful.
Example: Prices of college textbooks

26. Levels of Measurement Nominal - categories only
Ordinal - categories with some order
Interval - differences but no natural starting point
Ratio - differences and a natural starting point
review of four levels of measurement

27. Levels of Measurement Nominal - categories only
Ordinal - categories with some order
Interval - differences but no natural starting point
Ratio - differences and a natural starting point