Pivot Table Working with Excel (2010). What can we do with a pivot table ?  Creating a pivot table  Connection between variables  Calculate data (sum,

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Presentation transcript:

Pivot Table Working with Excel (2010)

What can we do with a pivot table ?  Creating a pivot table  Connection between variables  Calculate data (sum, average,…)  Manage interval range  Differentiate data

What can we do with a pivot table ?  Graphs: Histogram / Bar chart  Select interval width.  Eliminate bar gap.  Present cumulative graphs.

What can we do with a pivot table ?  Filter/differentiate data  Eliminate un-necessary values by explanatory variable.  Eliminate un-necessary values by external variable.

Creating a Pivot-Table Working with Excel (2010) – Pivot table

Creating a pivot table in Excel (2010) Step 1: Select the data you which to organize

Creating a pivot table in Excel (2010) Step 2: Choose “insert” tab in the menu. Click on “Pivot table”

Creating a pivot table in Excel (2010) Step 3: The table “range is the data you previously selected”.

Creating a pivot table in Excel (2010) Step 3: Choose if the table appears in a new worksheet or in a specific square in the current worksheet.

Creating a pivot table in Excel (2010) An empty table has apeared. All the variables are in the top right corner.

Creating a pivot table in Excel (2010) There are 4 “windows” in which you can drag the variables…

Creating a pivot table in Excel (2010) Row labels The explanatory variable (X). If you want to know something, for every possible value of X.

Creating a pivot table in Excel (2010) Row labels The “age” variable has been presented as the X variable (explanatory). All its value are separated in the pivot table.

Creating a pivot table in Excel (2010)  Values Which calculations you want to perform on a variable, Y=f(X). f(X) can be sum of values, average value, count of occurrences (frequency). The calculations will be differentiated for every value of (X).

Creating a pivot table in Excel (2010)  Values For each age value (X i ) the sum grade (Y=f(X i )) is presented (default calculation option).

Creating a pivot table in Excel (2010)  Values – change calculation By left-clicking the calculated variable, a menu opens. Choose “Value field settings”

Creating a pivot table in Excel (2010)  Values – change calculation In the window, choose whatever form of calculation you whish to perform on the explanatory variable (X). Let’s choose “Count”.

Creating a pivot table in Excel (2010)  Values – change calculation The new pivot-table provides the number of observations for each age value.

Creating a pivot table in Excel (2010)  Values – change calculation Add another variable (or the same one, with different calculation). We get more data for each value of “Grade” (average, Min, Max…)

Creating a pivot table in Excel (2010) Column labels If the results of the calculation (f(X)) can be separated into sub- categories (by gender, by age). Differentiate when separating the calculations provides further data.

Creating a pivot table in Excel (2010) Column labels There are more male participants than females (29-23). How is the spread of results different between the genders ? (later …)

Creating a pivot table in Excel (2010) Report filter “Slice” the results for a certain portion of the population (age=17, height=1.83, country=ISR). In case some of the results, according to a third variable are irrelevant (but appear in the original data).

Creating a pivot table in Excel (2010) Report filter Let’s assume we check the average grade (f(X)) for men & women (X) … But we want to consider only a certain age group of

Creating a pivot table in Excel (2010) Report filter Click the arrow to open the box. Inclosed are all possible values “Age”. Click “Select multiple items”. Click “All” to select non. Then select only ages

Graphs: Histogram, Bar chart Cumulative graph Working with Excel (2010) – Pivot table

Graphs: Histogram & Bar chart  Reminder – both the histogram and the bar chart represent a count (frequency) of observations for a given value/range of explanatory data (X).  If the explained data (Y) is discrete (for example – age), use a Bar chart.  If Y is continuous (for example, grade), use Histogram.  Just connect the bars

Graphs: Create a frequency chart Step 1: Choose the same variable in the “Row lables” and “  Values” boxes. In this case – “Grade”.

Graphs: Create a frequency chart Step 2: Group the values of “Grade” into intervals. Right-click anywhere in the “grade” column. In the menu, choose “Group”.

Graphs: Create a frequency chart Step 3: Decide the length of each interval, the minimal and maximal values. In this case – 10 units.

Graphs: Create a frequency chart Step 4: Change the calculation of “Grade” to count:

Graphs: Create a frequency chart Step 5: Choose a “Pivot-Chart”. In the menu, choose “Clustered column”.

Graphs: Create a frequency chart Step 5: Now, eliminate the space between bars by right- clicking the bars. Choose “Format data axis”.

Graphs: Create a frequency chart Step 5: Switch the “no-gap” scale to zero.

Graphs: Create a frequency chart And Voilà !

Graphs: Create a cumulative graph Step 1: If we want a cumulative graph, we need to change the calculation to “Running total in”.

Graphs: Create a cumulative graph Step 2: From the new table created, we again create a pivot-chart.

Filter un-necessary data Working with Excel (2010) – Pivot table

Filter un-necessary data Let’s return to our table with many calculations for each grade interval. We are said that the interesting group are males from Additionally, we are told the grades under 54 are not relevant.

Filter un-necessary data Step 1: Eliminate un-necessary data from explanatory variable. Let’s eliminate from the table data regarding grades <55.

Filter un-necessary data Step 1: Click the arrow of the “Grade” column in the table. Un-click the “<45” and “45- 54” boxes.

Filter un-necessary data Step 2: Eliminate un-necessary data from external (gender) variable. Drag “Gender” to “report filer” box.

Filter un-necessary data Step 2: Click the arrow to open the “gender” values. Un-click “Female”.

Filter un-necessary data Any differences ? Before After