Methods of Communication
Research and Statistics
Online Workbook
|
SPSS exercise 2.8
Open the MediaUse.sav database.
a. Use the variables 'v5hour' and 'v5min', calculate the average number of minutes the respondents spend watching television on a working day. A new variable will have to be made for this in order to convert the viewing time in hours into minutes. Put the syntax into the answer field.
b. What level of measurement does this variable have?
c. Calculate the mean and the standard deviation. Round it off to two decimal places and draw a conclusion. When giving your answer, you must include the following: the 'content' of the variable, the units of analysis, the correct number for the measure of central tendency (round off to two decimals), and the interpretation of the measure of central tendency.
d. What are the minimum and maximum values of this variable?
Hints
1 Creating a new variable based on multiple existing variables
When you want to convert two or more variables into one variable, use the Compute function in SPSS. Compute is SPSS's 'calculator'; it can be used to add, subtract and multiply variables, etc. Compute can only be used when the level of measurement of the variable is at least ordinal.
In the Transform menu, click Compute. This will open a screen: 'Compute variable'. In the 'Target variable' field, enter the name of the new variable that you want to create. You now need to define the formula for calculating the values of the new variable. The 'numeric expression' field now contains the formula. You can do this by typing or using the mouse to select the variables and symbols. When you have finished, click OK.
2 Measures of central tendency and measures of dispersion selection chart
| |
Measure of central tendency |
Mode |
Median |
Mean |
| Measure of dispersion |
|
Interquartile range |
Standard deviation, Variance |
| 1. Select |
1.1 Specifics |
What occurs most frequently? |
What is the median value? |
What is the balance point of the distribution? |
| 1.2 Minimum level of measurement |
Nominal |
Ordinal |
Interval |
| 1.3 Shape of the distribution |
Usable with every distribution shape |
Usable with every distribution shape |
Not optimal for very skewed distributions |
| 2. Calculate |
Analyze-> Descriptive Statistics -> Frequencies -> Statistics |
Analyze-> Descriptive Statistics -> Frequencies -> Statistics |
Analyze-> Descriptive Statistics -> Frequencies -> Statistics |
| 3. Check |
Unusable with a distribution with many peaks, e.g. in the case of an ungrouped interval variable. |
|
The greater the difference between the mode, median, and the mean, the more skewed the distribution. |
| 4. Conclude |
General:
1. Give your reasons for selecting the measure of central tendency and measure of dispersion (see Select and Check).
2. Use the value of the measure of dispersion to comment on the accuracy of the calculated measure of central tendency: the smaller the distribution, the better the centre typifies the distribution. |
| Mode: "The most common value of variable X is A.". |
Median: "The median value of variable X is A" or "Half of the units of analysis have A or less on variable X, and half of the units of analysis have A or more on variable X."
Interquartile range: "The mean deviation from variable X compared to the median is A" or "The middle half of the observations lies between (first quartile limit) and (third quartile limit).
|
Mean: "The units have an average A on variable X."
Standard deviation, Variance "The mean deviation in relation to the mean."
|
3 What do we mean by the standard deviation, the variance, and the interquartile range?
The standard deviation, the variance, and the interquartile range are all measures of dispersion. A measure of dispersion is a number that shows how far apart the results are from each other and/or from the mean. One number therefore serves to demonstrate the usefulness of the mean.
The standard deviation is the most commonly used measure of dispersion. It is calculated by extracting the root from the variance. The greater the standard deviation, the more the values differ from each other, and the fewer values that equal the mean there are. Analyse -> Descriptive Statistics -> Frequencies -> Statistics -> Std.deviation
Quartile: a quarter of the observations are below the first quartile; three-quarters of the observations are below the third quartile. The interquartile range is calculated as follows: the third quartile (percentile 75) minus the first quartile (percentile 25), divided by 2. Analyse -> Descriptive Statistics -> Frequencies -> Statistics -> Quartiles
|