| Autore |
Herkenhoff Linda
|
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa |
New York, NY : , : Springer New York : , : Imprint : Springer, , 2013
|
| Descrizione fisica |
1 online resource (XIV, 417 p. 620 illus., 569 illus. in color.)
|
| Disciplina |
330.015195
|
| Soggetto topico |
Statistics
Statistics and Computing/Statistics Programs
Statistics for Business, Management, Economics, Finance, Insurance
Statistics, general
|
| ISBN |
1-4614-8423-5
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Data and Statistics -- Key Concepts -- Discussion -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 2: Introduction to Excel and Basic Charts -- Key Concepts -- Discussion -- Basic Concepts -- Start Up -- Adding Data Analysis Toolpak -- Excel Elements -- Entering Formulas -- Cell References -- Sorting Data -- Filtering Data -- Getting Excel Help -- Statistical Tools -- Predefined or Built-In Formulas -- Formatting Data -- Chart Wizard -- Formatting of Graphs -- Bar and Column Charts -- Pie Charts -- Line Charts and Area Charts -- Line Graph Example -- Area Chart Example -- Other Charts -- Bubble Chart -- Radar Chart -- PivotTables (Aka Crosstabs) -- Excel -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 3: Summarizing Data: Descriptive Statistics and Histograms -- Key Concepts -- Discussion -- Symbols -- The Histogram -- Excel -- Descriptive Statistics -- Descriptive Output Results -- Changing the Width of the Column Output -- Using Excel Functions -- Histograms -- Example Problem -- Setting Up the Bin Ranges -- Creating the Histogram Chart -- Histogram Clean Up -- Closing Gaps Between Bars -- Change Labels on x-axis -- Removing More from the Chart and Labeling the Last Column -- Remove Legend -- Axes Labels -- Moving Axes Labels -- Changing the Bar Color -- Changing Chart Title -- Changing Chart Background Fill -- Rotating the y-axis Label from Vertical to Horizontal -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 4: Normal Distributions.
Key Concepts -- Discussion -- Excel -- Outline placeholder -- 1. Percentile Calculation Problems (NORM.DIST) -- (a) Calculating the area to the left of a value -- What % of the Time Did You Deliver to Less Than () 90 Stores During Last December and January? In Other Words How Much Data Is... -- (b) Calculating the area between 2 values -- What % of the Time Did You Deliver Fire Logs to Between 90 and 120 Stores During Last December and January? -- (c) Calculating the area to the right of a value -- What % of Time Did You Deliver to 130 or More Stores ( \geq ) During Last December and January? In Other Words How Much Da... -- (d) Graphing a normal distribution (Area Graph) -- Step 1 -- Step 2 -- Step 3 -- 2. Converting Percentiles to Measured Units (NORM.INV) -- Calculate the Number of Stores Corresponding with the 99th Percentile -- 3. Converting Measured Units to z-Scores (STANDARDIZE) -- Convert the Measured Value of 135 Stores to a z-Score -- 4. Calculate Rank and Percentile (Rank and Percentile) -- Outline placeholder -- Output -- 5. Non-normal Distributions -- Calculate What Percentage of Rents Fall Between 409 and 573 -- Step 1: Convert the Measured Values to Standard Units -- Step 2: Use Chebyshev Approximation=1-(1/(k)2) where k is the boundary value in standard units -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 5: Survey Design -- Key Concepts -- Discussion -- Basic Concepts -- Survey Design -- Scale -- Types of Questions -- Single Response/Select -- Multiple Response/Select -- Structured Questions -- Ranking and Rating -- Non-structured (Open-Ended) Questions -- Data -- Labels -- Demographic Data -- Response Rates -- Editing: Data Quality -- Coding -- Errors in Survey Question Creation -- Loaded Questions.
Leading Questions -- Double-Barreled Questions -- Errors in Survey Data Collection -- Random Sampling Error -- Systematic Error -- Response Bias -- Checklist -- Excel -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 6: Sampling -- Key Concepts -- Discussion -- Types of Problems -- Mean versus proportion problems require slightly different treatment -- Finite versus infinite population size is another important factor in determining the appropriate sample size -- Rules of thumb -- Excel -- Problem Type: Infinite Mean -- Practice Problem for Infinite Mean -- Problem Type: Infinite Proportion -- Practice Problem for Infinite Proportion -- Finite Population Correction Factor (fpc) -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 7: Inference -- Key Concepts -- Discussion -- Inferring Proportions -- Example Problem -- Excel -- Inferring Averages -- Example Problem -- Excel -- Confidence Intervals with Proportion Inference -- Example Problem -- Excel -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 8: Probability -- Key Concepts -- Discussion -- Example 1 -- Example 2 -- Excel -- Finding Probabilities Using Normal Distributions -- What Is the Probability That a Dealership Will Sell 90 Cars or Less (x90) per Week? -- What Is the Probability That a Car Dealership Will Sell at least 130 (x130) Cars per Week? -- What Is the Probability That a Car Dealership Will Sell Between 90 and 120 Cars per Week? -- Calculating Combinations and Permutations -- Permutation -- Combination -- Finding Probabilities Using the Binomial Distribution.
Royal Bank Retention Problem -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 9: Correlation -- Key Concepts -- Discussion -- Nonlinear data caution -- Average data caution -- Excel -- Correlation: One r Value or Correlation Matrix -- Method 1: Two or More Data Sets (Matrix) -- Method 2: Only 2 Data Sets -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 10: Simple Linear Regression -- Key Concepts -- Discussion -- Residuals and Tests for Linearity -- Standardized Residuals and Outliers -- Excel -- Scatterplot: Compute the Regression Line and the Coefficient of Determination -- Regression Function: Compute the Regression Model -- Compute Residual Plots Using the Regression Function -- Using Excel´s Regression Tool to Test for Normality of the Distribution of Residuals -- Method 1: Normal Probability Plot -- Method 2: Normal Distribution of Residuals -- Using Excel´s Regression Tool to Test for Constant Variance of Residuals -- Summary of Regression Analysis Process -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activities -- Parting Thought -- Problem Solutions -- Chapter 11: Significance Tests Part 1 -- Key Concepts -- Discussion -- Basic Concepts -- Choosing the Appropriate Significance Test -- One-Tailed Tests -- Two-Tailed Tests -- Significance Tests -- F-test -- Basic Descriptions of F-Test Applications -- Example 1: One-Way Repeated Measures Using ANOVA -- Example 2: Regression Problems -- Example 3: F-Test for Equality of Two Variances -- Example 4: Between Group ANOVA -- Excel -- Example 1: One-Way Repeated Measures Using ANOVA.
Example 2: Regression -- Example 3: Two Sample for Variances -- One-Tailed F-Test for Two Sample for Variances -- Two-Tailed F-Test for Equality of Two Variances -- Example 4: Between Group ANOVA -- One-Tail F-Test Between Group ANOVA -- Two-Tail F-Test Between Group ANOVA -- t-Test -- Basic Descriptions of t-Test Applications -- Example 1: Regression Problems -- Example 2: t-Test for Equality of Means -- Example 3: t-TEST Paired Samples -- Excel -- Example 1: Regression Problems -- Example 2: t-Test for Equality of Means -- One-Tailed Test -- Two-Tailed Test -- Example 3: Before-After Models -- One-Tailed Test -- Two-Tailed Test -- T.TEST -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 12: Significance Tests Part 2 -- Key Concepts -- Discussion -- Significance Tests -- X2 Test -- Example 1: Goodness-of-Fit Test -- Example 2: Independence of Two Variables -- Excel -- Example 1: Goodness of Fit -- Example 2: Testing Independence -- z-Test -- Excel -- Example 1: Z-Test One Sample Mean Versus a Standard -- One-Tailed Results -- Two-Tailed Results -- Example 2: Testing the Means of Two Populations -- Z.TEST Tool for Comparing a Mean or Proportion with a Standard -- Example Problem -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 13: Multiple Regression -- Key Concepts -- Discussion -- Excel -- Step 1: Fit the Model with Selected Independent Variables -- Step 2: Does Multicollinearity Exist? Run a Correlation Matrix -- Step 3: Run Regression Model -- Step 4: Are the Assumptions of Regression Satisfied? -- Step 5: Test Overall Model Significance (F-Test).
Step 6: Check p-Values for Independent Variables Meet Significance Criteria (t-Test).
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| Record Nr. | UNINA-9910437878003321 |
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Analytics boot camp : basic analytics for business students andprofessionals / / Linda Herkenhoff and John Fogli
