1. COMMUNICATION ARTS RESEARCH CA3011 A. Parichart W. and A. Chulamani C.

2. Objectives  To introduce ways and tools for managing and analysing quantitative communication research data.  To introduce the steps involved in preparing quantitative data from a survey for computer analysis  To discuss the use of SPSS for the statistical examination of dat.

3. How to enter data

4. Types of numeric codes

5. Two Types of Numeric Codes  They are used for the kinds if variables that you will find on a survey questionnaire coding schedule:  Continuous variables (real number variables: Answers are recorded in terms of ‘real’ numbers. Ex. 28 years of age, 165 centimeters tall.  Categorical variables: Answers are recorded in terms of arbitrary or nominal ‘codes’ Ex. Gender; male (the code=1), female (the code=2) String variable (text variable) for the open-ended question

6. Case, Variable, Values

7. Variable View

8. Data View

9. Case, Variable and Values  Each row in the Data View window represents a case. In a survey, a ‘case’ would normally be the individual respondent/person interviewed.  Each column represents a variable. Ex. Age of the respondent, income, newspaper read Each variable in a survey can take on a number of values. EX. Gender using the values ‘1’ for male and ‘2’ for female.

10. Example

11. Defining Variables and Entering Data  The ‘Variable View’ screen shows, in each row, the detailed definitions relating to each variable, as follows: 1) Name (column 1): we enter a short name describing the first variable in our data set. 2) Type (column 2): click in the right-hand side of the cell and a dialogue box croups up, allowing us to choose from a set of types, including Numeric (the default choice), Date, String, etc. 3) Width (column 3): refers to the width of the data column; in most cases this can be left as it is.

12. Defining Variables and Entering Data 4) Decimals (column 4): most variables in content analyses or surveys are likely to be coded using the integers, that is whole numbers, so for clarity the default of 2 Decimals should be changed to ‘0’. Click in the cell, and use the up/down arrow that appears to choose 0 (zero) instead of the default 2. 5) Label (column 5): this allows us to enter a longer label than the single brief name entered in column 1, to describe what the variable refers to. Ex. A variable name ‘ Program’ can be labeled ‘Title of news program’ to clarify that this refers to the title or name of the news program analyzed.

13. Defining Variables and Entering Data 6) Value (column 6): this is of key importance.  If the variable consists of continuous data/real numbers then it is ‘1’ means ‘1’, ‘2’ means ‘2’, etc.  For categorical data: the numbers represents codes.(Clicking in the right-hand side of the Values cell brings up a dialogue box that allows us to do this by defining a Label for each Value.  Ex. ‘1’=BBC 1 ‘2’=BB2 ‘3’=Channel 4

14. Example

15. How to key in?

16. Example : Coding 1. What is your gender? ____ male ____ female 2. What is your status? ___single____married____divorced____separate

17. Example: Coding 3. Please rank the television channel you like most? ___ channel 3 ___ channel 5 ___ channel 7 ___ channel 9 ___ channel 11

18. Example: Coding 4. Please write a television program that you like most ____________

19. Analyzing Data with SPSS

20. Analysing Data  This is an interesting part of the research.  The first thing one would often want to do is to get a general ‘feel’ for what the data show- a general ‘feel’ for the distribution of different variables in the data set. Ex. How many men and female were there in the research? What was their average age? What percentages of men and women respectively user Twitter?

21. Frequencies and Descriptives  We begin to get a good picture of the distribution of individual variables with two types of SPSS analysis:  One for analysing the frequencies of individual values in a variable,  The other for a descriptive summary of the values of a variable in terms of calculating the average (also known as the mean value) of the values of a variable and showing its minimum and maximum values.

22. 1. Menu Selections: Frequencies  Analyze > Descriptive Statistics> Frequencies The variables analyzed with the Frequencies command are categorical variables consisting of the code numbers

23. Instruction  To describe the gender of consumers

25. Example

26. 2. Menu Selections: Descriptive  It makes sense to summarize the data which is not the categorical variable, but consists of the real numbers as the average or total items.  In a survey this may be the age, height, weight of respondents, choose the Analyze>Descriptive Statistics> Descriptives Frequencies & descriptives – for describing and summarizing individual variables.

27. Instruction  To find the mean scores of the satisfaction of product A

29. Example

30. Crosstab & Mean

31. 3. Menu Selections: Crosstabs  In SPSS, a command that could compare two or more variables with each other.  Crosstabs- for comparing categorical variables  Analyze> Descriptive Statistics>Crosstabs IF ONE VARIABLE HAS MORE VALUES THAN THE OTHER, PUT THIS VARIABLE (THE ONE WITH MORE VALUES) IN THE "ROW" BOX; PUT THE OTHER VARIABLE (THE ONE WITH LESS VALUES) IN THE "COLUMN” BOX IF ONE VARIABLE HAS MORE VALUES THAN THE OTHER, PUT THIS VARIABLE (THE ONE WITH MORE VALUES) IN THE "ROW" BOX; PUT THE OTHER VARIABLE (THE ONE WITH LESS VALUES) IN THE "COLUMN” BOX

32. Instruction  To compare gender with type of shopper

33. Example

37. 4. Menu Selections: Compare Means  In SPSS, a command that could compare a continuous variable across the categorical variable. Analyze>Compare Means>Means The dependent variable is a continuous variable consisting of many values; independent variable is a categorical variable

38. Instruction  To compare the satisfaction of product A between gender

41. Reference  Hansen, A., & Machin, D. (2013). Media and Communication Research Methods. Basingstoke: Palgrave Macmillan.

42. Thank you for your attention

43. In-class exercise