Excel and research

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USING MICROSOFT EXCEL WITH BUSINESS RESEARCH METHODS www.drjayeshpatidar.blogspot.com

Transcript of Excel and research

Page 1: Excel and research

USING MICROSOFT EXCEL WITH BUSINESS RESEARCH METHODS

www.drjayeshpatidar.blogspot.com

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TITLE BAR

MENU BAR

FORMULA BAR

STANDARD TOOLBAR

FORMATTING TOOLBAR

ACTIVE CELL

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PASTE FUNCTION

TOOLS MENU

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The Paste Function Provides Numerous Statistical

Operations

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The Statistical Function Category

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Data Analysis Dialog Box

• Click on “Tools”• Select “Data Analysis”• Select statistical operation

o such as Histogram

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Functions

• Functions are predefined formulas for mathematical operations

• They perform calculations by using specific values, called arguments

• Arguments indicate data or a range of cells

• Arguments are performed, in a particular order, called the syntax.

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Functions

• Functions are predefined formulas for mathematical operations

• They perform calculations by using specific values, called arguments

• Arguments are performed, in a particular order, called the syntax.

• For example, the SUM function adds values or ranges of cells

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Easy to Use Paste Functions

• AVERAGE (MEAN)• MEDIAN• MODE• SUM• STANDARD DEVIATION

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Functions

• The syntax of a function begins with the function name

• followed by an opening parenthesis• the arguments for the function • separated by commas• a closing parenthesis. • If the function starts a formula, an equal

sign (=) is typed before the function name.

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The Equal Sign Then The Function Name And

Arguments

• =FUNCTION (Argument1)• =FUNCTION (Argument1,Argument2)

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Arguments

• Typical arguments are numbers, text, arrays, and cell references.

• Arguments can also be constants, formulas, or other functions.

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The AVERAGE Function Located in the Statistical Category

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Data Array

• The data appear in cells A2 through 14• A2:A14• Sometimes written with dollars signs• $A$2:$A$14

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Sum, Average, and Standard Deviation

• =FUNCTION (Argument1)• =SUM(A2:A9)• =AVERAGE(A2:A9)• =STDEVA(A2:A9)

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SUM FunctionSales Call Example

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AVERAGE (Mean) FunctionSales Call Example

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Standard Deviation FunctionSales Call Example

Variance s2: (algebraic, scalable computation)

Standard deviation s is the square root of variance s2

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• Variance

• Standard deviation: the square root of the variance

– Measures spread about the mean

– It is zero if and only if all the values are equal

– Both the deviation and the variance are algebraic

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Data Dispersion Characteristics

• Motivation

– To better understand the data: central tendency, variation and spread

• Data dispersion characteristics

– median, max, min, quantiles, outliers, variance, etc.

• Numerical dimensions correspond to sorted intervals

– Data dispersion: analyzed with multiple granularities of precision

– Boxplot or quantile analysis on sorted intervals

• Dispersion analysis on computed measures

– Folding measures into numerical dimensions

– Boxplot or quantile analysis on the transformed cube

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Measuring the Central Tendency

• Mean

– Weighted arithmetic mean

• Median: A holistic measure

– Middle value if odd number of values, or average of the middle two

values otherwise

– estimated by interpolation

• Mode

– Value that occurs most frequently in the data

– Unimodal, bimodal, trimodal

– Empirical formula:

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Measuring the Dispersion of Data

• Quartiles, outliers and boxplots

– Quartiles: Q1 (25th percentile), Q3 (75th percentile)

– Inter-quartile range: IQR = Q3 – Q1

– Five number summary: min, Q1, M, Q3, max

– Boxplot: ends of the box are the quartiles, median is marked, whiskers,

and plot outlier individually

– Outlier: usually, a value higher/lower than 1.5 x IQR

• Variance and standard deviation

– Variance s2: (algebraic, scalable computation)

– Standard deviation s is the square root of variance s2

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Boxplot Analysis

• Five-number summary of a distribution:

Minimum, Q1, M, Q3, Maximum

• Boxplot

– Data is represented with a box

– The ends of the box are at the first and third quartiles, i.e., the height of the box is IRQ

– The median is marked by a line within the box

– Whiskers: two lines outside the box extend to Minimum and Maximum

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A Boxplot

A boxplot

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Visualization of Data Dispersion:

Boxplot Analysis

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Mining Descriptive Statistical Measures in Large

Databases

• Variance

• Standard deviation: the square root of the variance

– Measures spread about the mean

– It is zero if and only if all the values are equal

– Both the deviation and the variance are algebraic

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Histogram Analysis

• Graph displays of basic statistical class descriptions

– Frequency histograms

• A univariate graphical method

• Consists of a set of rectangles that reflect the counts or frequencies of

the classes present in the given data

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Quantile Plot

• Displays all of the data (allowing the user to assess both the overall behavior and unusual occurrences)

• Plots quantile information

– For a data xi data sorted in increasing order, fi indicates that approximately 100 fi% of the data are below or equal to the value xi

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Quantile-Quantile (Q-Q) Plot

• Graphs the quantiles of one univariate distribution against

the corresponding quantiles of another

• Allows the user to view whether there is a shift in going from

one distribution to another

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Scatter plot

• Provides a first look at bivariate data to see clusters of

points, outliers, etc

• Each pair of values is treated as a pair of coordinates and

plotted as points in the plane

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Loess Curve

• Adds a smooth curve to a scatter plot in order to provide

better perception of the pattern of dependence

• Loess curve is fitted by setting two parameters: a smoothing

parameter, and the degree of the polynomials that are fitted

by the regression

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Graphic Displays of Basic Statistical

Descriptions

• Histogram: (shown before)

• Boxplot: (covered before)

• Quantile plot: each value xi is paired with fi indicating that

approximately 100 fi % of data are xi

• Quantile-quantile (q-q) plot: graphs the quantiles of one

univariant distribution against the corresponding quantiles of

another

• Scatter plot: each pair of values is a pair of coordinates and

plotted as points in the plane

• Loess (local regression) curve: add a smooth curve to a

scatter plot to provide better perception of the pattern of

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Proportion

• =COUNT• =COUNTIF• DIVIDE COUNTIF BY COUNT• =D3/D2

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Frequency Distributions

• There are alternative ways of constructing frequency distributions

• COUNTIF function• HISTOGRAM function

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=COUNTIF(A6:A134,1)=D4/D9*100

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Histogram Function

• Tools -Data Analysis-Histogram• Bins

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The bins are thefrequency categories

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Insert Input and Bin Ranges

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Text Labels Can Be Included or Excluded From Input Range

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The Chart Wizard

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The Descriptive Statistics Function

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SEVERAL ROWS OF DATA ARE HIDDEN

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SEVERAL ROWS OF DATA ARE HIDDEN

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Correlation

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Correlation Coefficient, r = .75

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Regression Analysis

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