BOOK NAME: Statistical Analysis With Microsoft Excel Wonderfull Ebook on Microsoft Excel having 256 pages.Available in pdf format.People who want to do Ph.D in any subject like Ecnomics,chemistry,Physics,Computer Science,Forensic Science,Biotechnology,Bioinformatics,Statistics should read this eBook.This eBook is very easy to read,no computer knowledge is required,only you need a computer and Microsoft Excel. Writing Formulas 1.1 The Basics Of Writing Formulae 1.2 Tool For Using This Effectively: Viewing The Formula Instead Of The End Result The “A1” Vs. The “R1C1“ Style Of Cell References Writing A Simple Formula That References Cells 1.3 Types Of References Allowed In A Formula Referencing Cells From Another Worksheet Referencing A Block Of Cells Referencing Non–Adjacent Cells Referencing Entire Rows Referencing Entire Columns Referencing Corresponding Blocks Of Cells/Rows/Columns From A Set Of Worksheets 2 Copying/Cutting And Pasting Formulae 2.1 Copying And Pasting A Formula To Other Cells In The Same Column 2.2 Copying And Pasting A Formula To Other Cells In The Same Row 2.3 Copying And Pasting A Formula To Other Cells In A Different Row And Column 2.4 Controlling Cell Reference Behavior When Copying And Pasting Formulae (Use Of The “$” Key) Using The “$” Sign In Different Permutations And Computations In A Formula 2.5 Copying And Pasting Formulas From One Worksheet To Another 2.6 Pasting One Formula To Many Cells, Columns, Rows 2.7 Pasting Several Formulas To A Symmetric But Larger Range 2.8 Defining And Referencing A “Named Range” 2.9 Selecting All Cells With Formulas That Evaluate To A Similar Number Type 2.10 Special Paste Options Pasting Only The Formula (But Not The Formatting And Comments) Pasting The Result Of A Formula, But Not The Formula Itself 2.11 Cutting And Pasting Formulae The Difference Between “Copying And Pasting” Formulas And “Cutting And Pasting” Formulas 2.12 Creating A Table Of Formulas Using Data/Table 2.13 Saving Time By Writing, Copying And Pasting Formulas On Several Worksheets Simultaneously 3 Paste Special 3.1 Pasting The Result Of A Formula, But Not The Formula 3.2 Other Selective Pasting Options Pasting Only The Formula (But Not The Formatting And Comments) Pasting Only Formats Pasting Data Validation Schemes Pasting All But The Borders Pasting Comments Only 3.3 Performing An Algebraic “Operation” When Pasting One Column/Row/Range On To Another Multiplying/Dividing/Subtracting/Adding All Cells In A Range By A Number Multiplying/Dividing The Cell Values In Cells In Several “Pasted On” Columns With The Values Of The Copied Range 3.4 Switching Rows To Columns 4 Inserting Functions 4.1 Basics 4.2 A Simple Function 4.3 Functions That Need Multiple Range References 4.4 Writing A “Function Within A Function” 4.5 New Function-Related Features In The XP Version Of Excel Enhanced Formula Bar Error Checking And Debugging 5 Tracing Cell References & Debugging Formula Errors 5.1 Tracing The Cell References Used In A Formula 5.2 Tracing The Formulas In Which A Particular Cell Is Referenced 5.3 The Auditing Toolbar 5.4 Watch Window (Only Available In The XP Version Of Excel) 5.5 Error Checking And Formula Evaluator (Only Available In The XP Version Of Excel) 5.6 Formula Auditing Mode (Only Available In The XP Version Of Excel) 5.7 Cell-Specific Error Checking And Debugging 5.8 Error Checking Options 6 Functions For Basic Statistics 6.1 “Averaged” Measures Of Central Tendency AVERAGE TRIMMEAN (“Trimmed Mean”) HARMEAN (“Harmonic Mean”) GEOMEAN (“Geometric Mean”) 6.2 Location Measures Of Central Tendency (Mode, Median) MEDIAN MODE 6.3 Other Location Parameters (Maximum, Percentiles, Quartiles, Other) QUARTILE PERCENTILE Maximum, Minimum And “Kth Largest” Rank Or Relative Standing Of Each Cell Within The Range Of A Series 6.4 Measures Of Dispersion (Standard Deviation & Variance) 6.5 Shape Attributes Of The Density Function (Skewness, Kurtosis) Skewness Kurtosis 6.6 Functions Ending With An “A” Suffix 7 Probability Density Functions And Confidence Intervals 7.1 Probability Density Functions (Pdf), Cumulative Density Functions (Cdf), And Inverse Functions Probability Density Function (PDF) Cumulative Density Function (CDF) Inverse Mapping Functions 7.2 Normal Density Function The Probability Density Function (PDF) And Cumulative Density Function (CDF) Inverse Function Confidence Intervals 7.3 Standard Normal Or Z–Density Function 7.4 T–Density Function One–Tailed Confidence Intervals 7.5 F–Density Function 7.6 Chi-Square Density Function 7.7 Other Continuous Density Functions: Beta, Gamma, Exponential, Poisson, Weibull & Fisher Beta Density Function Gamma Density Function Exponential Density Function Fisher Density Function Poisson Density Function Weibull Density Function Discrete Probabilities— Binomial, Hypergeometric & Negative Binomial 7.8 List Of Density Function 7.9 Some Inverse Function 8 Other Mathematics & Statistics Functions 8.1 Counting And Summing 8.2 The “If” Counting And Summing Functions: Statistical Functions With Logical Conditions 8.3 Transformations (Log, Exponential, Absolute, Sum, Etc) 8.4 Deviations From The Mean 8.5 Cross Series Relations Covariance And Correlation Functions Sum Of Squares 9 Add-Ins: Enhancing Excel 9.1 Add-Ins: Introduction What Can An Add-In Do? Why Use An Add-In? 9.2 Add–Ins Installed With Excel 9.3 Other Add-Ins 9.4 The Statistics Add-In Choosing The Add-Ins 10 Statistics Tools 10.1 Descriptive Statistics 10.2 Rank And Percentile 10.3 Bivariate Relations— Correlation, Covariance Covariance Tool And Formula 11 Hypothesis Testing 11.1 Z-Testing For Population Means When Population Variances Are Known 11.2 T-Testing Means When The Two Samples Are From Distinct Groups The Pretest— F-Testing For Equality In Variances T-Test: Two–Sample Assuming Unequal Variances T-Test: Two–Sample Assuming Equal Variances 11.3 Paired Sample T-Tests 11.4 Anova 12 Regression 12.1 Assumptions Underlying Regression Models Assumption 1: The Relationship Between Any One Independent Series And The Dependent Series Can Be Captured By A Straight Line In A 2–Axis Graph Assumption 2: The Independent Variables Do Not Change If The Sampling Is Replicated Assumption 3: The Sample Size Must Be Greater Than The Number Of Independent Variables (N Should Be Greater Than K–1) Assumption 4: Not All The Values Of Any One Independent Series Can Be The Same Assumption 5: The Residual Or Disturbance Error Terms Follow Several Rules Assumption 6: There Are No Strong Linear Relationships Among The Independent Variables 12.2 Conducting The Regression 12.3 Brief Guideline For Interpreting Regression Output 12.4 Breakdown Of Classical Assumptions: Validation And Correction 13 Other Tools For Statistics 13.1 Sampling Analysis 13.2 Random Number Generation 13.3 Time Series 14 The SOLVER Tool For Constrained Linear Optimization 14.1 Defining The Objective Function (Choosing The Optimization Criterion) 14.2 Adding Constraints 14.3 Choosing Algorithm Options Offer Price Today!

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