Excel and research

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  • USING MICROSOFT EXCEL WITH BUSINESS RESEARCH METHODS www.drjayeshpatidar.blogspot.com
  • TITLE BAR MENU BAR FORMULA BAR STANDARD TOOLBAR FORMATTING TOOLBAR ACTIVE CELL
  • PASTE FUNCTION TOOLS MENU
  • The Paste Function Provides Numerous Statistical Operations
  • The Statistical Function Category
  • Data Analysis Dialog Box Click on Tools Select Data Analysis Select statistical operation o such as Histogram
  • 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.
  • 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
  • Easy to Use Paste Functions AVERAGE (MEAN) MEDIAN MODE SUM STANDARD DEVIATION
  • 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.
  • The Equal Sign Then The Function Name And Arguments =FUNCTION (Argument1) =FUNCTION (Argument1,Argument2)
  • Arguments Typical arguments are numbers, text, arrays, and cell references. Arguments can also be constants, formulas, or other functions.
  • The AVERAGE Function Located in the Statistical Category
  • Data Array The data appear in cells A2 through 14 A2:A14 Sometimes written with dollars signs $A$2:$A$14
  • Sum, Average, and Standard Deviation =FUNCTION (Argument1) =SUM(A2:A9) =AVERAGE(A2:A9) =STDEVA(A2:A9)
  • SUM Function Sales Call Example
  • AVERAGE (Mean) Function Sales Call Example
  • Standard Deviation Function Sales Call Example Variance s2: (algebraic, scalable computation) Standard deviation s is the square root of variance s2 n i n i ii n i i x n x n xx n s 1 1 22 1 22 ])( 1 [ 1 1 )( 1 1
  • 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 26www.drjayeshpatidar.blogspot.com
  • 27 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 www.drjayeshpatidar.blogspot.com
  • 28 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: n i ix n x 1 1 n i i n i ii w xw x 1 1 )(3 medianmeanmodemean www.drjayeshpatidar.blogspot.com
  • 29 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 n i n i ii n i i x n x n xx n s 1 1 22 1 22 ])( 1 [ 1 1 )( 1 1 www.drjayeshpatidar.blogspot.com
  • 30 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 www.drjayeshpatidar.blogspot.com
  • 31 A Boxplot A boxplot www.drjayeshpatidar.blogspot.com
  • 32 Visualization of Data Dispersion: Boxplot Analysis www.drjayeshpatidar.blogspot.com
  • 33 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 22 1 22 1 1 1 )( 1 1 ii n i i x n x n xx n s www.drjayeshpatidar.blogspot.com
  • 34 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 www.drjayeshpatidar.blogspot.com
  • 35 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 www.drjayeshpatidar.blogspot.com
  • 36 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 www.drjayeshpatidar.blogspot.com
  • 37 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 www.drjayeshpatidar.blogspot.com
  • 38 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 www.drjayeshpatidar.blogspot.com
  • 39 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 dependence www.drjayeshpatidar.blogspot.com
  • Proportion =COUNT =COUNTIF DIVIDE COUNTIF BY COUNT =D3/D2
  • Frequency Distributions There are alternative ways of constructing frequency distributions COUNTIF function HISTOGRAM function
  • =COUNTIF(A6:A134,1) =D4/D9*100
  • Histogram Function Tools -Data Analysis-Histogram Bins
  • The bins are the frequency categories
  • Insert Input and Bin Ranges
  • Text Labels Can Be Included or Excluded From Input Range
  • The Chart Wizard
  • The Descriptive Statistics Function