Download presentation

1
**BUS 220: ELEMENTARY STATISTICS**

Chapter 1: What is statistics?

2
**GOALS The importance of statistics**

The difference between descriptive statistics and inferential statistics. The difference between qualitative variable and quantitative variable. The difference between discrete variable and continuous variable. The distinction among nominal, ordinal, interval, and ratio levels of measurement. The difference between sample and population and why sampling is sometimes needed. 3/28/2017

3
**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 3/28/2017

4
**What is Meant by Statistics?**

Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions. 3/28/2017

5
Who Uses Statistics? Statistical techniques are used extensively by marketing, accounting, quality control, consumers, professional sports people, hospital administrators, educators, politicians, physicians, etc... 3/28/2017

6
**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 3/28/2017

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, “I’ve 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! You’re 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.” 3/28/2017 BUS220/Sophea Chea

8
**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 2007. Inferential Statistics: The methods used to estimate a property of a population on the basis of a sample. 3/28/2017

9
**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 parameter statistic 3/28/2017

10
Why sampling is needed? Prohibitive costs in terms of financial and physical Destruction of the sample in a sampling process Reliability of inferential statistics 3/28/2017

11
**For each of the following determine whether the group is a sample or a population**

The participants in a study of a new cholesterol drug The drivers who received a speeding ticket in Kansas City last month Those on welfare in Cook County (Illinois) The 30 stocks reported as a part of the Dow Jones Industrial Average 3/28/2017 BUS220/Sophea Chea

12
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. 3/28/2017

13
**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. 3/28/2017

14
**Summary of Types of Variables**

3/28/2017

15
3/28/2017

16
**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 manufacturer’s representatives per month. 3/28/2017

17
**Summary of the Characteristics for Levels of Measurement**

3/28/2017

18
**What is the level of measurement for each of the following variables?**

Student IQ ratings Distance students travel to class Student scores on the first statistics test A classification of student by state of birth A ranking of students as freshman, sophomore, junior, and senior Number of hours students study per week 3/28/2017 BUS220/Sophea Chea

19
**Rating of a finance professor Number of home computers**

Salary Gender Sales volume Soft drink preference Temperature SAT scores Student rank in class Rating of a finance professor Number of home computers Table I Discrete Variable Continuous Variable Qualitative 1- 2- Quantitative 3- 4- a Table II Discrete Variable Continuous Variable Nominal 5 6 Ordinal 7 8 Interval 9 10 Ratio 11 12- a 3/28/2017 BUS220/Sophea Chea

Similar presentations

OK

1 1 Slide Chapter 1 Data and Statistics n Applications in Business and Economics n Data n Data Sources n Descriptive Statistics n Statistical Inference.

1 1 Slide Chapter 1 Data and Statistics n Applications in Business and Economics n Data n Data Sources n Descriptive Statistics n Statistical Inference.

© 2018 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google