This document contains summaries of various Excel data analysis techniques including: text to columns to separate cell content into different columns based on delimiters; pivot tables to analyze data from different perspectives; scatter plots and linear regression to determine relationships between variables; installing the Analysis ToolPak add-in; descriptive statistics like measures of central tendency, variance, skewness, and kurtosis; correlation to examine relationships between variables; and regression to make predictions by modeling relationships between independent and dependent variables with lines and equations.

1. By Khaled Al-Shamaa

2. Text to Columns (1)
 Use the Convert Text to Columns Wizard to separate
simple cell content, such as first names and last
names, into different columns.
 Depending on your data, you can split the cell content
based on a delimiter, such as a space or a comma, or
based on a specific column break location within your
data.
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3. Text to Columns (2)
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4. Pivot Table (1)
 A pivot table is a cross-tabulation, it is another way of
looking at the data.
 The importance of pivot tables is that they allow you to
get your hands dirty with the data. By dropping fields
into and out of the table, you might see relationships
and carry out analyses that might not occur to you if
you just look at the original database.
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5. Pivot Table (2)
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6. Pivot Table (3)
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7. Advanced Scatter Plot (1)
 We linear regression to determine the relationship
between one variable, x, and another variable, y.
 The scatter plot is a graph that represents each
individual measured on both x and y as a point.
 Right-click any of the points in the scatter plot will open
the pop-up menu, select "Add Trendline" option to open
a dialog box. Select the Linear radio button and click the
Display Equation and Display R-Squared checkboxes.
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8. Advanced Scatter Plot (2)
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9. Installing Analysis ToolPak (1)
 To install an Add-In in Excel 2007 you need to click the
Office button and press the Excel Options button.
 From the options dialog select the Add-In section.
Select Excel-Add-ins from the Manage drop list and
then press the Go... button.
 From the Add-Ins dialog select Analysis ToolPak
checkbox then click on OK button.
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10. Installing Analysis ToolPak (2)
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11. Descriptive Statistics (1)
 Measures of central tendency and variability are good
ways of summarizing data, but they aren’t the only ways.
 Some descriptive statistics are intuitive (like count,
max, min), some are not (like skewness and kurtosis).
 The variance tells you how spread out the scores are.
 Skewness indicates how symmetrically the scores are
distributed.
 Kurtosis shows you whether or not your scores are
distributed with a peak in the neighborhood of the mean.
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12. Descriptive Statistics (2)
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13. Correlation (1)
 Correlation is a statistical way of looking at a
relationship. When two things are correlated, it means
that they vary together:
 A correlation of –1 represents perfect negative correlation.
 A correlation of +1 represents perfect positive correlation.
 A correlation of 0 means that the two variables are not
related.
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14. Correlation (2)
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15. Regression (1)
 One of the main things you do when you work with
statistics is make predictions. The idea is to take data on
one or more variables, and use these data to predict a
value of another variable.
 In mathematics, a line is a way to picture a relationship
between an independent variable (x) and a dependent
variable (y). The slope (a) is the number that multiplies
x and the intercept (b) is the number you add to x.
y=a+b.x
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16. Regression (2)
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17. Thank You
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