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Lectures one and two What is Statistics? Lecturer: Dr. Madgerie Jameson

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1 Lectures one and two What is Statistics? Lecturer: Dr. Madgerie Jameson Madgerie.Jameson@sta.uwi.edu

2 Opening Example Where do you shop for clothes and shoes? Do you have a favourite store you shop at? If yes, Why do you shop there? Do you think television commercials have a part to play in your choice of shop? In the US a study was conducted by the National Retail Federation found that 18% of the adults they surveyed said that television commercials influenced them to shop at specific stores. What do you think?

3 Definition of Statistics A set of tools and techniques that is used for describing, organising and interpreting information or data (Salkind, 2008, p.7). The methods used to collect, organise, summarise, analyse, interpret and draw collusions from a given data set.

4 StatisticsDescriptiveInferential

5 Descriptive Statistics Used to collect, organise, summarise and present a data set usually presented in graphically. For example the following table shows the names of 12 students and their M.Ed majors. You can use the descriptive data to find the most popular choice of subject., the average of students enrolled in the course.

6 StudentMajorAgeStudentMajorAge JoeyReading35BillCurriculum30 SarahCurriculum27JaneScience Ed45 AltheaYouth Guidance47JeffreyScience Ed27 NicoleScience Ed50PaulineReading40 MichaelCurriculum40LouiseReading34 ElizabethScience Ed27JordanScience Ed35

7 Inferential Statistics Are used to make inferences from a given data set. Inferential statistics are often the next step after you have collected and summarised data. Inferential Statistics are used to 1. Make generalisations from the sample to the population using probabilities. 2. Perform hypothesis testing. 3. Determine relationships among groups. 4. Make predictions.

8 Example Inferential Statistics Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

9 POPULATION VERSUS SAMPLE  Definition  A population consists of all elements – individuals, items, or objects – whose characteristics are being studied. The population that is being studied is also called the target population.  A portion of the population selected for study is referred to as a sample. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

10 Figure 1.1 Population and Sample Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

11 Population Population: Includes all objects of interest. That is the complete set of data elements. For example, In the previous example the population of students would be all the students enrolled in Physics, Chemistry and Biology ( 50 students) Parameter: Usually seen as the characteristics of the population and denoted with the Greek Letter [ mu (µ), sigma (σ)]

12 Sample Sample: A sample is a portion of the population selected for further analysis, For example, you may decide to use 20 out of the 50 students for further analysis. Statistics: are associated with the sample and are usually denoted using the roman letters ( x, s).

13 Example Assume there are 80 students in the research methods class. 20 of the 80 students major is Youth Guidance. Since 20 is 25% of 80, we can say 25% of the students enrolled in the M.Ed programme major in youth guidance. The 25% is a parameter ( not a statistic) of the class because it is based on the entire population of M.Ed students. If we assume that the M.Ed programme is a representative of the entire post graduate programme we treat the 20 students as a sample drawn from a larger population of post graduate students ( Dip Ed, M.Phil) then the 25% becomes a statistic.

14 POPULATION VERSUS SAMPLE  Definition  A survey that includes every member of the population is called a census. The technique of collecting information from a portion of the population is called a sample survey. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

15 Example of Sample Survey Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

16 POPULATION VERSUS SAMPLE  Definition  A sample that represents the characteristics of the population as closely as possible is called a representative sample. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

17 POPULATION VERSUS SAMPLE  Definition  A sample drawn in such a way that each element of the population has a chance of being selected is called a random sample. If all samples of the same size selected from a population have the same chance of being selected, we call it simple random sampling. Such a sample is called a simple random sample. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

18 BASIC TERMS  Definition  An element or member of a sample or population is a specific subject or object (for example, a person, firm, item, state, or country) about which the information is collected. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

19 BASIC TERMS  Definition  A variable is a characteristic under study that assumes different values for different elements. In contrast to a variable, the value of a constant is fixed. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

20 BASIC TERMS  Definition  The value of a variable for an element is called an observation or measurement.  A data set is a collection of observations on one or more variables. Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

21 Example Charitable Donations of Six Retailers in 2007 Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

22 Data Facts, observations and information that come from research. Data types Measurement Data are numeric (quantitative). Categorical data are non numeric ( qualitative).

23 Variable Definition: Characteristic or attribute that can assume different values Types of Variables Independent Variable: one that is manipulated, measured or selected by the researcher. Dependent variable: one that is not under the researcher’s control. It is observed and measured. Random variable: A variable whose values are determined by chance.

24 SUMMATION NOTATION  A sample of prices of five literary books:  $75, $80, $35, $97, and $88  The variable price of a book: x  Price of the first book = x 1 = $75  Price of the second book = x 2 = $80  …  Adding the prices of all five books gives  75+80+35+97+88 = x 1 +x 2 +x 3 +x 4 +x 5 = Σx Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

25 Example  Annual salaries (in thousands of dollars) of four workers are 75, 90, 125, and 61, respectively. Find (a) ∑x (b) (∑x)² (c) ∑x² Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

26 Solution (a) ∑x = x 1 + x 2 + x 3 + x 4 = 75 + 90 + 125 + 61 = 351 = $351,000 (b) (∑x)² = (351)² = 123,201 (c) ∑x² = (75)² + (90)² + (125)² + (61)² = 5,625 + 8,100 + 15,625 + 3,721 = 33,071 Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

27 Example 2 The following table lists four pairs of m and f values: Compute the following: (a) Σm (b) Σf² (c) Σmf (d) Σm²f Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

28 Example 2: Solution Prem Mann, Introductory Statistics, 7/E Copyright © 2010 John Wiley & Sons. All right reserved

29 Entering data in Excel http://www.youtube.com/watch?v=3DGxbNf-fyA/

30 Summary Statistics is a tool that helps us understand our world. This is done through the organisation of data that we have collected that permits us to make certain statements about how the features of the data can be related to other settings. Descriptive and inferential statistics work together. The type of statistics you use depends on the questions you want answered.


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