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BUS 220: ELEMENTARY STATISTICS Chapter 1: What is statistics?

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Presentation on theme: "BUS 220: ELEMENTARY STATISTICS Chapter 1: What is statistics?"— Presentation transcript:

1 BUS 220: ELEMENTARY STATISTICS Chapter 1: What is statistics?

2 2/15/20142 GOALS 1. The importance of statistics 2. The difference between descriptive statistics and inferential statistics. 3. The difference between qualitative variable and quantitative variable. 4. The difference between discrete variable and continuous variable. 5. The distinction among nominal, ordinal, interval, and ratio levels of measurement. 6. The difference between sample and population and why sampling is sometimes needed.

3 2/15/20143 Why Study Statistics? Numerical information is everywhere Statistical techniques are used to make decisions that affect our daily lives No matter what your career, you will make professional decisions that involve data

4 2/15/20144 What is Meant by Statistics? Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions.

5 2/15/20145 Who Uses Statistics? Statistical techniques are used extensively by marketing, accounting, quality control, consumers, professional sports people, hospital administrators, educators, politicians, physicians, etc...

6 2/15/20146 How do they use statistics? A marketing research analyst needs to assess the effectiveness of a new television campaign A pharmaceutical manufacturer needs to determine whether a new drug is more effective than the current one An operations manager wants to find out whether the quality of a product is conforming to company standard

7 That must have been a statistician Three men are in a hot-air balloon. Soon, they find themselves lost in a canyon somewhere. One of the three men says, Ive got an idea. We can call for help in this canyon and the echo will carry our voices far. So he leans over the basket and yells out, Helllloooooo! Where are we? They hear the echo several times.) Fifteen minutes pass. Then they hear this echoing voice: Helllloooooo! Youre lost!! One of the men says, That must have been a statistician. Puzzled, one of the other men asks, Why do you say that? The reply: For three reasons. (1) he took a long time to answer, (2) he was absolutely correct, and (3) his answer was absolutely useless. 2/15/2014 BUS220/Sophea Chea 7

8 2/15/20148 Types of Statistics – Descriptive Statistics Descriptive Statistics - Methods of organizing, summarizing, and presenting data in an informative way. EXAMPLE: According to the Bureau of Labor Statistics, the average hourly earnings of construction workers were $20.60 for February Inferential Statistics: The methods used to estimate a property of a population on the basis of a sample.

9 2/15/20149 Population versus Sample A population is the entire set of individuals or objects of interest. A sample is a portion, or part, of the population of interest statistic parameter

10 2/15/ Why sampling is needed? Prohibitive costs in terms of financial and physical Destruction of the sample in a sampling process Reliability of inferential statistics

11 For each of the following determine whether the group is a sample or a population A. The participants in a study of a new cholesterol drug B. The drivers who received a speeding ticket in Kansas City last month C. Those on welfare in Cook County (Illinois) D. The 30 stocks reported as a part of the Dow Jones Industrial Average 2/15/2014 BUS220/Sophea Chea 11

12 2/15/ Types of Variables A. Qualitative or Attribute variable or Categorical variable - the characteristic being studied is nonnumeric. EXAMPLES: Gender, religious affiliation, type of automobile owned, state of birth, eye color. B. Quantitative variable or Numerical variable - information is reported numerically. EXAMPLES: Balance in your checking account, minutes remaining in class, or number of children in a family.

13 2/15/ Quantitative Variables - Classifications Quantitative variables can be classified as either discrete or continuous. A. Discrete variables: can only assume certain values and there are usually gaps between values. EXAMPLE: the number of bedrooms in a house, or the number of hammers sold at the local Home Depot (1,2,3,…,etc). B. Continuous variables: can assume any value within a specified range. EXAMPLE: The pressure in a tire, the weight of a pork chop, or the height of students in a class.

14 2/15/ Summary of Types of Variables

15 2/15/201415

16 2/15/ Four Levels of Measurement Nominal level – They can be categorized eye color, gender, religious affiliation. Ordinal level – Can they be arranged in some order? Y During a taste test of 4 soft drinks, Mellow Yellow was ranked number 1, Sprite number 2, Seven-up number 3, and Orange Crush number 4. Interval level - Are there meaningful amounts of differences between data values? Y Temperature on the Fahrenheit scale. Ratio level – Is there natural zero point? Y Monthly income of surgeons, or distance traveled by manufacturers representatives per month.

17 2/15/ Summary of the Characteristics for Levels of Measurement

18 What is the level of measurement for each of the following variables? A. Student IQ ratings B. Distance students travel to class C. Student scores on the first statistics test D. A classification of student by state of birth E. A ranking of students as freshman, sophomore, junior, and senior F. Number of hours students study per week 2/15/2014 BUS220/Sophea Chea 18

19 Table IDiscrete Variable Continuous Variable Qualitative1-2- Quantitative3-4- a 2/15/2014 BUS220/Sophea Chea 19 Table IIDiscrete Variable Continuous Variable Nominal56 Ordinal78 Interval910 Ratio1112- a a)Salary b)Gender c)Sales volume d)Soft drink preference e)Temperature f)SAT scores g)Student rank in class h)Rating of a finance professor i)Number of home computers

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