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What is Meant by Statistics?

What is Meant by Statistics?. Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions. COPAID. Types of Statistics. Descriptive Statistics. Inferential Statistics.

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What is Meant by Statistics?

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  1. What is Meant by Statistics? Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions. COPAID

  2. Types of Statistics Descriptive Statistics Inferential Statistics

  3. Descriptive Statistics deals withmethods of Organizing, Summarizing, & Presenting data*in an informative way. • Typically, descriptive statistics include • Mean, • Mode, • Median, • Variance, • Deviation, • Skewness, • Charts – histogram, bar, pie • (we will see these in later chapters) * past/current data but not estimated future data

  4. Excel Example Output of Descriptive Statistics

  5. Inferential Statistics: methods used todetermine something about a population on the basis ofa sample. Population– all possible individuals, objects. Sample –part of the population of interest

  6. Why sample? • Time & cost are prohibitive • Physical impossibility of checking all items in population • (eg. Checking quality of product if they are made in the millions) • Destructive nature of some tests • Sample results are adequate for decision-making

  7. Types of Variables

  8. Types of Variables For a Qualitative or Attribute Variable the characteristic being studied is non-numeric. It can only be labeled. (sometimes also called Categorical variable)

  9. Types of Variables In a Quantitative Variable information is reported numerically. Balance in your checking account Minutes remaining in class Number of children in a family

  10. Types of Quantitative Variables Quantitative variables can be classified as eitherDiscrete or Continuous. Discrete Variables:can only assume certain values -there are usually “gaps” between values - usually “counted” Example: the number of bedrooms in a house, or the number of hammers sold at the local Home Depot (1,2,3,…,etc).

  11. A Continuous Variable can assume any value within a specified range (“no gaps”). The pressure in a tire The height or weight of students in a class.

  12. Chart to remember

  13. Levels of Measurement • Nominal • Ordinal • Interval • Ratio The level of measurement dictates the kind of calculations you can do on the data. Eg. If one student’s major is Accounting and another’s IS, we cannot calculate the average major. On the other hand, we can average their heights, weights, etc.

  14. Nominal level Data that is classified into categories. Can be arranged in any order. Measurement consists only of counts.

  15. In this example, Country or Region is Nominal Level data Other examples: religion, major, gender, ethnicity, …

  16. Nominal level data must be: Mutually exclusive An individual, object, or measurement is included in only one category. Exhaustive Each individual, object, or measurement must appear in one of the categories.

  17. Ordinal level - involves data arranged in some order - magnitude of differences between data values cannot be determined. During a taste test of 4 soft drinks, Coca Cola was ranked number 1, Dr. Pepper number 2, Pepsi number 3, and Root Beer number 4.

  18. Example of an Ordinal level variable Also, see the example table in page 12 (Homeland Security Advisory System)

  19. Interval level - similar to the ordinal level - amounts of differences between data values is of equal size - there is no natural zero point. • Eg. • Temperature on the Fahrenheit scale. • Difference between 10°F - 15°F is same as between50°F& - 55°F • 0° does not represent absence of temperature

  20. Ratio level (“highest” level of measurement) - zero value means “absence” - differences and ratios are meaningful for this level of measurement (A person with $2Million is twice as rich as another with $1Million) Monthly income ‘0’ means did not make any money Traveled ‘0’ miles means did not travel at all

  21. ( Nerd Of India Rocks! ) N-O-I-R

  22. Ethical Considerations • Statistics can be used to mislead decision makers • Don’t do it! • Keep taking different samples until you get the result you want • Quote ‘average’ to hide wide range of data values • Misleading graphical outputs • Make unwarranted conclusions on variable relationships

  23. Ethical Considerations The cost/year doubled in 5 years. But the graph appears to depict more than that.

  24. Ethical Considerations By changing the x-y scale, the rate of change in unemployment appears different.

  25. Ethical Considerations • Also, a statistical association between two variables does not automatically imply ‘causation’. More in Chapter 13. • Eg. • Consumption of peanuts is correlated with aspirin consumption (eating peanuts gives headaches)

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