1. 1 Introduction to Statistics Chapter 1 MSIS 111 Prof. Nick Dedeke

2. 2 Objectives Define statistics Differentiate between descriptive and inferential statistics Define statistical variables Classifying numbers

3. 3 What is Statistics? A general way to view statistics is as follows: it is a language and the set of rules that enables us to make sense of data about events, people, places and things.

4. 4 Valid Statistic?: Example 1 An online survey conducted recently leads to the conclusion that Apple’s iphone product will not succeed in the U.S. market. 75% of the men and 89% of the women answered “never” when asked the question: Would you buy an ipod?

5. 5 Valid Statistic?: Example 2 When you vote consider this information. A mail survey showed that in the years when Democrats controlled the Congress, U.S. had a higher number of destructive level 5 hurricanes. In the years that the Republicans controlled Congress, the U.S. have more days with extremely cold and extremely hot days.

6. 6 Valid Statistic?: Example 3 If you are seeking to have a job quickly after you graduate, do not wear a clothing with the color white during your interview. A recent phone survey of fifty human resources managers at the top 10 retail firms in America revealed that only 2% of them wear white clothing to work.

7. 7 Fact There is such a thing as bad statistics You can always make bad statistics say anything you want it to say The cure for bad statistics is good statistics

8. 8 Do we need really need statistics? Imagine a government never gathers data about population growth. Imagine a hospital that never stores data about patient data and care Imagine a car firm that never analyzes data about vehicle rollovers Imagine an insurance firm that never interprets the causes for the increases in health care costs

9. 9 Definition of statistics? Statistics is a science dealing with the collection, organization, analysis, interpretation and presentation of quantitative and qualitative data. Statistics is a means to an end. The objective is not statistics for its own sake, it is the effective use of statistics for decision-making that matters for firms.

10. 10 Challenge of statistics? Statistics has two primary challenges: Describing a group of data with fewer data. For example, we have over 300 million U.S. citizens. I have the question for you. How tall are Americans? This kind is called descriptive statistics. Generating conclusions about a large group of data using smaller set from the same or related group. For example, I have the question: At which rate are we depleting fishes in our rivers? This kind is called inferential statistics.

11. 11 Terminologies in statistics? Statistics has two primary challenges: Census: Gather data from every member of a group or population, e.g. all voters in a presidential election, all subscribers to cable TV Sample: A randomly sampled set of members of a population Variable: Attribute of interest of each member of group Observation or measurement: The value of a variable for a member of a group (population or sample)

12. 12 Exercise 1: How many members are in this data set? Bill, Marty, Mary, Sue, Buba, Dub, Anne, Ali Baba, Jane, Phil, Don, Monki

13. 13 Exercise 2 For each of the underlined variables write down an example of what the observation would be when you survey a member of the population.

14. 14 Data Measurement The question that one puts on a survey determines how an attribute is measured. Consider the following questions: How much income do you make per year (in thousand $)? Do you make more than the US national average of $30,000 per year? [Yes] [No] How much income do you make per year? [Below $10k] [$10k to $30k] [$30k to $50k] [$50k to $70k] [above $70k]

15. 15 Data Measurement Many attributes could be measured at different levels. Ratio level. Absolute zero and ratio of numbers are meaningful How much income do you make per year (in thousand $)? Ratio level. Absolute zero and ratio of numbers are meaningful Nominal level. Grouping only and ranking not possible Do you make more than the US national average of $30,000 per year? [Yes] [No] Nominal level. Grouping only and ranking not possible Ordinal level. Absolute zero not emphasized and ranking possible How much income do you make per year? [Below $10k] [$10k to $30k] [$30k to $50k] [$50k to $70k] [above $70k] Ordinal level. Absolute zero not emphasized and ranking possible

16. 16 Exercise3: Data Measurement What kind of level of measurements are the following observations: