Christina Gustafsson. Introductory Guide to SAS Enterprise Guide 6.1 Part II

Transcription

1 Christina Gustafsson Introductory Guide to SAS Enterprise Guide 6.1 Part II 6. GRAPHS Bar Chart Pie Chart Histogram Scatterplot Boxplot Bar Chart for Two Categorical Variables Editing a Graph... 13

2 1 6. GRAPHS Graphs are handy tools to outline the distribution of a variable or the relations between two or several variables. When creating a graph, it s necessary to recognize the levels of measurement of the variables. Variables that are measured on nominal and ordinal level are referred to as categorical or qualitative variables. Qualitative variables are always discrete. Variables that are measured on interval and ratio level are referred to as quantitative variables. Some of quantitative variables are continuous ones. Next, let s look through some graphs you can often apply to your data set. It s quite easy to create a graph in EG, once you have learn the basics. You start to create a graph simply by selecting Tasks > Graph and then you can select which kind of graph you want to create.. Some of the statistical tasks can also generate a simple graph. With One-Way Frequencies task you can create either a simple vertical or horizontal bar chart. With Summary Statistics task you can create a histogram and a box and whiskers plot (= boxplot). With Distribution Analysis task you can also create a histogram and a boxplot. When you are creating a graph, you can usually define the layout of your graph by using some layout or appearance options in your graph task. You can edit your graphs in EG afterwards, only if your result format is either HTML or RTF. You can start to edit a graph by right-clicking it, and then select some option from the pull-down menu to edit the graph.

3 Bar Chart Bar chart is often used to summarize the values of a categorical variable. It is often used in exploratory data analysis to illustrate the basic features of the distribution. It displays the data using a number of rectangles, of the same width, each of which represents a particular category. Usually the length of each rectangle is proportional to the number of cases in the category it represents, but sometimes you need to create a bar chart, for example, to illustrate the mean of a certain variable in the groups of a certain categorical variable. You start the task by selecting Graph > Bar Chart. A Bar Chart window opens and now you can select the type of the bar chart you want to create by double-clicking the type icon (e.g. Simple Horizontal Bar). You usually create a horizontal bar chart for a variable that is measured either on nominal or ordinal level, and a vertical bar chart for a variable that is measured either on interval or ratio level. If you want to create a histogram graph for a continuous variable, you can do it in EG by using the Bar Chart task. In the Data tab you assign your variables. The values of the variable that you assign to the role Column to chart determine the number of different bars (e.g. math). If you assign a variable to the role Sum of, then that variable determines the lengths of the bars. You can choose the particular statistic (for example average) that is used to determine bar length by selecting the statistic in the Advanced tab. If you do not assign a variable to the role Sum of, then the frequency of each value of the Column to chart variable determines the lengths of the bars. If you assign a variable to the

4 3 role Group charts by, separate charts are generated for each group that are determined by the values of the variable that you assign to this role. In the Bars tab, you can specify the colors in your bar chart, and you can specify the number of bars, too. By default, the number of bars is determined automatically. For numeric variables, the values are divided into ranges, with one bar for each range. However, if the numeric variable represents discrete values, it is usually good idea to select the One bar for each unique data value option, because this selection creates a separate bar for each unique value of the variable. If you select the Enter number of bars option, the values of a numeric variable is divided into the number of ranges that you specify, and this selection creates a separate bar for each range. If you select Specify the bar values, then you can enter the values of individual bars by typing in the each values in the text box and click Add.

5 4 In the Layout tab, you can select whether to create a two-dimensional chart (2D checked) or a three-dimensional chart (uncheck the 2D check box). For three-dimensional charts you can select a bar shape from the Shape drop-down list. You can specify the sort order for the bars by using the Order drop-down list. By default, the sort order is determined automatically. You can choose to arrange the bars in ascending or descending order of height. If your Column to chart variable is measured at nominal level, then usually a descending order is used. If your variable is measured on ordinal level, then there is no point to change the order. In the Advanced tab, you can select from the Statistic used to calculate bar drop-down list the statistic to use in order to calculate the height of each bar. The available statistics depend on the type of graph that you are creating. If you did not assign a variable to the role Sum of, then the Frequency, Cumulative frequency, Percentage and Cumulative percentage statistics are available. If you assigned a variable to the role Sum of, then the Sum and Average statistics are available. If you have selected Average or Percentage as the statistic that is used to calculate the height of the bars, then you can select Display error bars to display confidence intervals on the bars. If you want to accept a missing value as a valid value for the chart variable, then check the Accept missing values check box. If you want to show the value of the statistic that is used to calculate the bar, check the Show statistics next to bar check box. To show the value of a statistic, check the Specify one statistical value to show for bars check box. Then select a statistic from the dropdown list. The statistic can be the same as or different from the statistic that is used to calculate the bar height. With the other tabs, you can change the layout of your graph, for instance, you can change the size of your chart and font types, a type in a title for your graph. Lastly click Run and here is the chart:

6 Pie Chart You usually use a pie chart to illustrate distribution of a categorical variable. It is a circle which is divided into slices. Each slice represents a particular category. The area of each slice is proportional to the number of cases in that category. You start to create a pie chart by selecting Graph > Pie Chart. A Pie Chart window opens and now you can select the type of the pie chart you want to create by double-clicking the type icon (e.g. Simple Pie). When you use the Pie Chart task, you can define the properties of your chart the same way you define the properties of a bar chart. So, for instance, in the Data tab you assign your variables, in the Pies tab, you can specify the number of slices. A simple pie chart of the variable math looks as follows:

7 Histogram A histogram is a way of summarizing especially a continuous quantitative variable. It divides up the range of possible values in a data set into classes or groups. For each group, a rectangle is constructed with a base length equal to the range of values in that specific group, and an area proportional to the number of observations falling into that group. One way to create a histogram, is to create a certain type of bar chart. So, select Graph > Bar Chart and Simple Vertical Bar. In the Data tab, assign the continuous variable to the role Column to Chart (e.g. age). In the Bars tab check Specify number of bars checkbox, and then select either Enter number of bars or Specify the bar values. If you select Enter number of bars, then specify the number of bars (usually 4 10, e.g. 7). If you select Specify the bar values, then specify the bar values. In the Layout tab, select from the Bar size pull-down menu Set spacing and specify the spacing as 0.

8 7 After clicking Run, the result looks like this: 6.4. Scatterplot A scatterplot is a useful summary of (usually) two quantitative variables, which is often created before working out a linear correlation coefficient or fitting a regression line. It gives a good visual picture of the relationship between the two variables, and helps the interpretation of the correlation coefficient or regression model. Each case contributes one point to the scatterplot, on which points are plotted but not joined. The resulting pattern indicates the type and strength of the relationship between the two variables. You start to create a scatterplot by selecting Graph > Scatter Plot. Again, you then select the type of the scatterplot you want to create (often 2D Scatter Plot). In the Data tab, you then must assign a Horizontal and a Vertical variable. The variable (e.g. attend1) that is assigned as the Horizontal variable is then X axis variable. The variable (e.g. attend2) that is assigned as the Vertical variable is then Y axis variable in your chart. If you want to create separate charts for each group of a certain variable, then you assign this variable as Group chars by variable. If you just want to create a simple scatterplot, then you can just click Run. If you would like to change the marker of your data points, you can do that in the Plots tab. If you would like to for

9 8 instance to fit a regression line to your scatterplot, then select Interpolations tab. The default Interpolation method is Scatter, which means that the plot consists just of the data points. If you select option Regression from the pull-down menu, then you can select the Type of the regression from a new pull-down menu. The default type is Linear. Here is a 2D scatterplot with a regression line: From the previous chart, you can see that the points tend to cluster around a straight line quite nicely. This means, that there is a strong linear relationship between the two variables. Because the line around which the points tends to cluster runs from lower left to upper right, the relationship between the two variables is positive (direct).

10 9 If the line around which the points tends to cluster runs from upper left to lower right, the relationship between the two variables is negative (inverse). If there exists a random scatter of points, there is no relationship between the two variables. If points clustering around a curve, not a straight line, then the relationship between the two variables is in non-linear. A scatterplot will also show up whether or not there exist any outliers in the data. If you want to create a scatterplot for two quantitative variables that has different types of markers for separate groups of a grouping variable, you have to start by selecting Graph > Line Plot. And the select Multiple line plots by group column as the type of the chart you going to create. In the Data tab assign your variables, again you must assign a Horizontal variable (e.g. attend1) and a Vertical variable (e.g. attend2), but yet you must assign a Group variable (e.g. gender), too. In the Interpolations tab, you can then select the Interpolations method as either Scatter (to create scatterplot) or Regression (to fit a regression line, too) for each of the groups, one by one.

11 10 The result of the previous task could look something like this: By the way, when you examine your charts in the Results tab, and you move your mouse pointer over some data point or line, you get some information about what are the variable values of that certain data point, or what is the equation for a certain regression line Boxplot A boxplot is a type of graph which is used to show the shape of the distribution, its central value, and variability. The basic boxplot produced consists of the most extreme values in the data set (maximum and minimum values), the lower and upper quartiles, and the median. You start to create a boxplot by selecting Graph > Box Plot. Then select Box Plot as the type of your graph. In the Data tab, you must assign some categorical variable as Horizontal variable (e.g. gender) and some quantitative variable as Vertical variable (e.g. exam).

12 11 There are several different types of boxplots. You can select in the Box Plot tab the type you want to create. For instance, if you want to create the basic boxplot, then from the Whisker length percentile pull-down menu, you can select high/low extremes. However, the most commonly used boxplot is the one, where the option times the interquartile range is used. And the result looks like this: It seems, that female students spend on average more time in studying for an exam than males students, because the median value of the exam is higher for female student than for male students.

13 Bar Chart for Two Categorical Variables If you want to check whether or not there is some kind of relationship between to categorical variables, there is usually no idea to create a scatterplot. You could try to create for instance a grouped bar chart. Select Graph > Bar Chart and for instance Grouped Colored Vertical Bar In the Data tab select then one of the variables as a Column to chart variable (e.g. math) and an other as Group bars by variable (e.g. gender). In the Bars tab select from Specify number of bars the option One bar for each unique data value. If you want to calculate the percentages of the Column to chart variable for each group of the grouping variable, then select in the Advanced tab first Percentage and then check Calculate percentages and cumulative percentages for each group.

14 13 The result looks like this: Because the percentual distribution of math does not look the same for male and female students, then there is some kind of relationship between math and gender Editing a Graph You can edit your graphs in EG afterwards, only if your result format is either HTML or RTF. You can start to edit a graph by right-clicking it and then select some option from the pop-up menu to edit the graph.

15 14 The options vary with the type of your graph. For instance, if you are editing a bar graph, you can change the direction of your bars by selecting Chart Type option, and with Graph Properties option you can change the shape of the bars. When you edit your graph, the changes will not be saved with your project. If you want to save the edited graph, you can do it by right-clicking the graph, and then select Save as and type in a name for your graph. You can also copy your graph by right-clicking the graph, and then select Copy. And the you can paste the copied graph for instance to some word processor.