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Biblioteca

MARC Lista (tabellare)
Excel 2019 for environmental sciences statistics : a guide to solving practical problems / / Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton
Excel 2019 for environmental sciences statistics : a guide to solving practical problems / / Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton
Autore Quirk Thomas J.
Edizione [Second edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (xvii, 250 pages) : illustrations
Disciplina 005.369
Collana Excel for Statistics
Soggetto topico Ciències ambientals
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-66277-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996466562503316
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Excel 2019 for environmental sciences statistics : a guide to solving practical problems / / Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton
Excel 2019 for environmental sciences statistics : a guide to solving practical problems / / Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton
Autore Quirk Thomas J.
Edizione [Second edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (xvii, 250 pages) : illustrations
Disciplina 005.369
Collana Excel for Statistics
Soggetto topico Ciències ambientals
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-66277-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910484650303321
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Excel 2019 for marketing statistics : a guide to solving practical problems / / Thomas J. Quirk, Eric Rhiney
Excel 2019 for marketing statistics : a guide to solving practical problems / / Thomas J. Quirk, Eric Rhiney
Autore Quirk Thomas J.
Edizione [Second edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (xix, 238 pages) : illustrations
Disciplina 005.369
Soggetto topico Màrqueting
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-62781-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996466546903316
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Excel 2019 for marketing statistics : a guide to solving practical problems / / Thomas J. Quirk, Eric Rhiney
Excel 2019 for marketing statistics : a guide to solving practical problems / / Thomas J. Quirk, Eric Rhiney
Autore Quirk Thomas J.
Edizione [Second edition.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (xix, 238 pages) : illustrations
Disciplina 005.369
Soggetto topico Màrqueting
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-62781-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910483778203321
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Excel 2019 for social work statistics : a guide to solving practical problems / / Thomas J. Quirk, Simone M. Cummings
Excel 2019 for social work statistics : a guide to solving practical problems / / Thomas J. Quirk, Simone M. Cummings
Autore Quirk Thomas J.
Edizione [2nd ed.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (273 pages)
Disciplina 519.5
Collana Excel for Statistics
Soggetto topico Social service - Statistical methods
Treball social
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-68257-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 1.1 Mean -- 1.2 Standard Deviation -- 1.3 Standard Error of the Mean -- 1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 1.4.1 Using the Fill/Series/Columns Commands -- 1.4.2 Changing the Width of a Column -- 1.4.3 Centering Information in a Range of Cells -- 1.4.4 Naming a Range of Cells -- 1.4.5 Finding the Sample Size Using the =COUNT Function -- 1.4.6 Finding the Mean Score Using the =AVERAGE Function -- 1.4.7 Finding the Standard Deviation Using the =STDEV Function -- 1.4.8 Finding the Standard Error of the Mean -- 1.4.8.1 Formatting Numbers in Number Format (Two Decimal Places) -- 1.5 Saving a Spreadsheet -- 1.6 Printing a Spreadsheet -- 1.7 Formatting Numbers in Currency Format (Two Decimal Places) -- 1.8 Formatting Numbers in Number Format (Three Decimal Places) -- 1.9 End-of-Chapter Practice Problems -- References -- Chapter 2: Random Number Generator -- 2.1 Creating Frame Numbers for Generating Random Numbers -- 2.2 Creating Random Numbers in an Excel Worksheet -- 2.3 Sorting Frame Numbers into a Random Sequence -- 2.4 Printing an Excel File So That All of the Information Fits Onto One Page -- 2.5 End-of-Chapter Practice Problems -- Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 3.1 Confidence Interval About the Mean -- 3.1.1 How to Estimate the Population Mean -- 3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean -- 3.1.3 Estimating the Confidence Interval for the Number of Outpatient Visits to a Clinic -- 3.1.4 Where Did the Number ``1.96´´ Come From? -- 3.1.5 Finding the Value for t in the Confidence Interval Formula.
3.1.6 Using Excel´s TINV Function to Find the Confidence Interval About the Mean -- 3.1.7 Using Excel to Find the 95% Confidence Interval for a Clinic´s Outpatient Visits -- 3.2 Hypothesis Testing -- 3.2.1 Hypotheses Always Refer to the Population That You Are Studying -- 3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis -- 3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used -- 3.2.3 The Seven Steps for Hypothesis Testing Using the Confidence Interval About the Mean -- 3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis -- 3.2.3.2 STEP 2: Select the Appropriate Statistical Test -- 3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test -- 3.2.3.4 STEP 4: Draw a Picture of the Confidence Interval About the Mean, Including the Mean, the Lower Limit of the Interval,... -- 3.2.3.5 STEP 5: Decide on a Decision Rule -- 3.2.3.6 STEP 6: State the Result of Your Statistical Test -- 3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! -- 3.3 Alternative Ways to Summarize the Result of a Hypothesis Test -- 3.3.1 Different Ways to Accept the Null Hypothesis -- 3.3.2 Different Ways to Reject the Null Hypothesis -- 3.4 End-of-Chapter Practice Problems -- References -- Chapter 4: One-Group t-Test for the Mean -- 4.1 The Seven STEPS for Hypothesis Testing Using the One-Group t-Test -- 4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis -- 4.1.2 STEP 2: Select the Appropriate Statistical Test -- 4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test -- 4.1.3.1 Finding the Absolute Value of a Number -- 4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test -- 4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E -- 4.1.6 STEP 6: State the Result of Your Statistical Test.
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! -- 4.2 One-Group t-Test for the Mean -- 4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? -- 4.4 End-of-Chapter Practice Problems -- References -- Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups -- 5.1 The Nine STEPS for Hypothesis Testing Using the Two-Group t-Test -- 5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 -- 5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group -- 5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test -- 5.1.4 STEP 4: Select the Appropriate Statistical Test -- 5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test -- 5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test -- 5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E -- 5.1.7.1 Find the Degrees of Freedom (df) for the Two-Group t-Test -- 5.1.8 STEP 8: State the Result of Your Statistical Test -- 5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! -- 5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis -- 5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis -- 5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30 -- 5.2.1 An Example of Formula #1 for the Two-Group t-Test -- 5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30 -- 5.4 End-of-Chapter Practice Problems -- References -- Chapter 6: Correlation and Simple Linear Regression -- 6.1 What Is a ``Correlation?´´ -- 6.1.1 Understanding the Formula for Computing a Correlation.
6.1.2 Understanding the Nine Steps for Computing a Correlation, r -- 6.2 Using Excel to Compute a Correlation Between Two Variables -- 6.3 Creating a Chart and Drawing the Regression Line onto the Chart -- 6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points -- 6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart -- 6.3.1.2 Moving the Chart Below the Table in the Spreadsheet -- 6.3.1.3 Making the Chart ``Longer´´ So That It Is ``Taller´´ -- 6.3.1.4 Making the Chart ``Wider´´ -- 6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page -- 6.5 Finding the Regression Equation -- 6.5.1 Installing the Data Analysis ToolPak into Excel -- 6.5.1.1 Installing the Data Analysis ToolPak into Excel 2019 -- 6.5.1.2 Installing the Data Analysis ToolPak into Excel 2016 -- 6.5.1.3 Installing the Data Analysis ToolPak into Excel 2013 -- 6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression -- 6.5.2.1 Finding the y-Intercept, a, of the Regression Line -- 6.5.2.2 Finding the Slope, b, of the Regression Line -- 6.5.3 Finding the Equation for the Regression Line -- 6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value -- 6.6 Adding the Regression Equation to the Chart -- 6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table -- 6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet -- 6.8.1 Printing Only the Table and the Chart on a Separate Page -- 6.8.2 Printing Only the Chart on a Separate Page -- 6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page -- 6.9 End-of-Chapter Practice Problems -- References -- Chapter 7: Multiple Correlation and Multiple Regression -- 7.1 Multiple Regression Equation -- 7.2 Finding the Multiple Correlation and the Multiple Regression Equation.
7.3 Using the Regression Equation to Predict FIRST-YEAR GPA -- 7.4 Using Excel to Create a Correlation Matrix in Multiple Regression -- 7.5 End-of-Chapter Practice Problems -- References -- Chapter 8: One-Way Analysis of Variance (ANOVA) -- 8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) -- 8.2 How to Interpret the ANOVA Table Correctly -- 8.3 Using the Decision Rule for the ANOVA F-Test -- 8.4 Testing for the Difference Between Two Groups Using the ANOVA t-Test -- 8.4.1 Comparing Clinic A vs. Clinic C in Time Required to Conduct an Initial Visit Using the ANOVA t-Test -- 8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test -- 8.4.1.2 Stating the Decision Rule for the ANOVA t-Test -- 8.4.1.3 Performing an ANOVA t-Test Using Excel Commands -- 8.5 End-of-Chapter Practice Problems -- References -- Appendices -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-Table -- Index.
Record Nr. UNISA-996466551603316
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Excel 2019 for social work statistics : a guide to solving practical problems / / Thomas J. Quirk, Simone M. Cummings
Excel 2019 for social work statistics : a guide to solving practical problems / / Thomas J. Quirk, Simone M. Cummings
Autore Quirk Thomas J.
Edizione [2nd ed.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (273 pages)
Disciplina 519.5
Collana Excel for Statistics
Soggetto topico Social service - Statistical methods
Treball social
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-68257-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 1.1 Mean -- 1.2 Standard Deviation -- 1.3 Standard Error of the Mean -- 1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 1.4.1 Using the Fill/Series/Columns Commands -- 1.4.2 Changing the Width of a Column -- 1.4.3 Centering Information in a Range of Cells -- 1.4.4 Naming a Range of Cells -- 1.4.5 Finding the Sample Size Using the =COUNT Function -- 1.4.6 Finding the Mean Score Using the =AVERAGE Function -- 1.4.7 Finding the Standard Deviation Using the =STDEV Function -- 1.4.8 Finding the Standard Error of the Mean -- 1.4.8.1 Formatting Numbers in Number Format (Two Decimal Places) -- 1.5 Saving a Spreadsheet -- 1.6 Printing a Spreadsheet -- 1.7 Formatting Numbers in Currency Format (Two Decimal Places) -- 1.8 Formatting Numbers in Number Format (Three Decimal Places) -- 1.9 End-of-Chapter Practice Problems -- References -- Chapter 2: Random Number Generator -- 2.1 Creating Frame Numbers for Generating Random Numbers -- 2.2 Creating Random Numbers in an Excel Worksheet -- 2.3 Sorting Frame Numbers into a Random Sequence -- 2.4 Printing an Excel File So That All of the Information Fits Onto One Page -- 2.5 End-of-Chapter Practice Problems -- Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 3.1 Confidence Interval About the Mean -- 3.1.1 How to Estimate the Population Mean -- 3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean -- 3.1.3 Estimating the Confidence Interval for the Number of Outpatient Visits to a Clinic -- 3.1.4 Where Did the Number ``1.96´´ Come From? -- 3.1.5 Finding the Value for t in the Confidence Interval Formula.
3.1.6 Using Excel´s TINV Function to Find the Confidence Interval About the Mean -- 3.1.7 Using Excel to Find the 95% Confidence Interval for a Clinic´s Outpatient Visits -- 3.2 Hypothesis Testing -- 3.2.1 Hypotheses Always Refer to the Population That You Are Studying -- 3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis -- 3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used -- 3.2.3 The Seven Steps for Hypothesis Testing Using the Confidence Interval About the Mean -- 3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis -- 3.2.3.2 STEP 2: Select the Appropriate Statistical Test -- 3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test -- 3.2.3.4 STEP 4: Draw a Picture of the Confidence Interval About the Mean, Including the Mean, the Lower Limit of the Interval,... -- 3.2.3.5 STEP 5: Decide on a Decision Rule -- 3.2.3.6 STEP 6: State the Result of Your Statistical Test -- 3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! -- 3.3 Alternative Ways to Summarize the Result of a Hypothesis Test -- 3.3.1 Different Ways to Accept the Null Hypothesis -- 3.3.2 Different Ways to Reject the Null Hypothesis -- 3.4 End-of-Chapter Practice Problems -- References -- Chapter 4: One-Group t-Test for the Mean -- 4.1 The Seven STEPS for Hypothesis Testing Using the One-Group t-Test -- 4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis -- 4.1.2 STEP 2: Select the Appropriate Statistical Test -- 4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test -- 4.1.3.1 Finding the Absolute Value of a Number -- 4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test -- 4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E -- 4.1.6 STEP 6: State the Result of Your Statistical Test.
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! -- 4.2 One-Group t-Test for the Mean -- 4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? -- 4.4 End-of-Chapter Practice Problems -- References -- Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups -- 5.1 The Nine STEPS for Hypothesis Testing Using the Two-Group t-Test -- 5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 -- 5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group -- 5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test -- 5.1.4 STEP 4: Select the Appropriate Statistical Test -- 5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test -- 5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test -- 5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E -- 5.1.7.1 Find the Degrees of Freedom (df) for the Two-Group t-Test -- 5.1.8 STEP 8: State the Result of Your Statistical Test -- 5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! -- 5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis -- 5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis -- 5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30 -- 5.2.1 An Example of Formula #1 for the Two-Group t-Test -- 5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30 -- 5.4 End-of-Chapter Practice Problems -- References -- Chapter 6: Correlation and Simple Linear Regression -- 6.1 What Is a ``Correlation?´´ -- 6.1.1 Understanding the Formula for Computing a Correlation.
6.1.2 Understanding the Nine Steps for Computing a Correlation, r -- 6.2 Using Excel to Compute a Correlation Between Two Variables -- 6.3 Creating a Chart and Drawing the Regression Line onto the Chart -- 6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points -- 6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart -- 6.3.1.2 Moving the Chart Below the Table in the Spreadsheet -- 6.3.1.3 Making the Chart ``Longer´´ So That It Is ``Taller´´ -- 6.3.1.4 Making the Chart ``Wider´´ -- 6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page -- 6.5 Finding the Regression Equation -- 6.5.1 Installing the Data Analysis ToolPak into Excel -- 6.5.1.1 Installing the Data Analysis ToolPak into Excel 2019 -- 6.5.1.2 Installing the Data Analysis ToolPak into Excel 2016 -- 6.5.1.3 Installing the Data Analysis ToolPak into Excel 2013 -- 6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression -- 6.5.2.1 Finding the y-Intercept, a, of the Regression Line -- 6.5.2.2 Finding the Slope, b, of the Regression Line -- 6.5.3 Finding the Equation for the Regression Line -- 6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value -- 6.6 Adding the Regression Equation to the Chart -- 6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table -- 6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet -- 6.8.1 Printing Only the Table and the Chart on a Separate Page -- 6.8.2 Printing Only the Chart on a Separate Page -- 6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page -- 6.9 End-of-Chapter Practice Problems -- References -- Chapter 7: Multiple Correlation and Multiple Regression -- 7.1 Multiple Regression Equation -- 7.2 Finding the Multiple Correlation and the Multiple Regression Equation.
7.3 Using the Regression Equation to Predict FIRST-YEAR GPA -- 7.4 Using Excel to Create a Correlation Matrix in Multiple Regression -- 7.5 End-of-Chapter Practice Problems -- References -- Chapter 8: One-Way Analysis of Variance (ANOVA) -- 8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) -- 8.2 How to Interpret the ANOVA Table Correctly -- 8.3 Using the Decision Rule for the ANOVA F-Test -- 8.4 Testing for the Difference Between Two Groups Using the ANOVA t-Test -- 8.4.1 Comparing Clinic A vs. Clinic C in Time Required to Conduct an Initial Visit Using the ANOVA t-Test -- 8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test -- 8.4.1.2 Stating the Decision Rule for the ANOVA t-Test -- 8.4.1.3 Performing an ANOVA t-Test Using Excel Commands -- 8.5 End-of-Chapter Practice Problems -- References -- Appendices -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-Table -- Index.
Record Nr. UNINA-9910483050803321
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Excel 2019 in applied statistics for high school students : a guide to solving practical problems / / Thomas J. Quirk
Excel 2019 in applied statistics for high school students : a guide to solving practical problems / / Thomas J. Quirk
Autore Quirk Thomas J.
Edizione [2nd ed. 2021.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (XVII, 244 p. 169 illus., 162 illus. in color.)
Disciplina 658.4033
Collana Excel for Statistics
Soggetto topico Management - Statistical methods
Gestió
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-66756-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgements -- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 2 Random Number Generator -- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 4 One-Group t-Test for the Mean -- 5 Two-Group t-Test of the Difference of the Means for Independent Groups -- 6 Correlation and Simple Linear Regression -- 7 Multiple Correlation and Multiple Regression -- 8 One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index.
Record Nr. UNISA-996466565303316
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Excel 2019 in applied statistics for high school students : a guide to solving practical problems / / Thomas J. Quirk
Excel 2019 in applied statistics for high school students : a guide to solving practical problems / / Thomas J. Quirk
Autore Quirk Thomas J.
Edizione [2nd ed. 2021.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (XVII, 244 p. 169 illus., 162 illus. in color.)
Disciplina 658.4033
Collana Excel for Statistics
Soggetto topico Management - Statistical methods
Gestió
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-66756-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Acknowledgements -- 1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- 2 Random Number Generator -- 3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- 4 One-Group t-Test for the Mean -- 5 Two-Group t-Test of the Difference of the Means for Independent Groups -- 6 Correlation and Simple Linear Regression -- 7 Multiple Correlation and Multiple Regression -- 8 One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index.
Record Nr. UNINA-9910483480903321
Quirk Thomas J.  
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Festschrift in honor of R. Dennis Cook : fifty years of contribution to statistical science / / Efstathia Bura, Bing Li, editors
Festschrift in honor of R. Dennis Cook : fifty years of contribution to statistical science / / Efstathia Bura, Bing Li, editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (200 pages)
Disciplina 519.5
Soggetto topico Statistics
Mathematical statistics
Estadística matemàtica
Soggetto genere / forma Homenatges
Llibres electrònics
ISBN 3-030-69009-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- A Tribute to Professor R. Dennis Cook -- Contents -- Using Mutual Information to Measure the Predictive Powerof Principal Components -- 1 Introduction -- 2 Overview of Previous Results -- 3 Conditional Mutual Information -- 3.1 Under the Linear Model -- 3.2 Beyond the Linear Regression Model -- 3.3 Beyond the Normal Distribution -- 4 Discussion -- References -- A Robust Estimation Approach for Mean-Shiftand Variance-Inflation Outliers -- 1 Introduction -- 2 Our Proposal and Some Background -- 2.1 A Generalized Setting -- 2.2 Some Technical Background -- 2.3 Our Proposal -- 2.4 Graphical Diagnostics -- 3 Simulation Study -- 4 Real-Data Examples -- 5 Final Remarks -- References -- Estimating Sufficient Dimension Reduction Spaces by Invariant Linear Operators -- 1 Introduction -- 2 Invariant Linear Operators -- 3 Invariant Linear Operator and Its Eigenvectors -- 4 Some Important Members of T Y|X -- 4.1 Sliced Average Variance Estimation -- 4.2 SIR-II -- 4.3 Contour Regression -- 4.4 Directional Regression -- 5 Two Estimation Methods Based on Invariant Operators -- 5.1 Iterative Invariant Transformations (IIT) -- 5.2 Nonparametrically Boosted Inverse Regression (NBIR) -- 6 Numerical Study -- 7 Concluding Remarks -- References -- Testing Model Utility for Single Index Models Under High Dimension -- 1 Introduction -- 2 Generalized SNR for Single Index Models -- 2.1 Notation -- 2.2 A Brief Review of the Sliced Inverse Regression (SIR) -- 2.3 Generalized Signal-to-Noise Ratio of Single Index Models -- 2.4 Global Testing for Single Index Models -- 3 The Optimal Test for Single Index Models -- 3.1 The Detection Boundary of Linear Regression -- 3.2 Single Index Models -- 3.3 Optimal Test for SIMa -- 3.4 Computationally Efficient Test -- 3.5 Practical Issues -- 4 Numerical Studies -- 5 Discussion -- Appendix: Proofs -- Assisting Lemmas.
Proof of Theorems -- References -- Sliced Inverse Regression for Spatial Data -- 1 Introduction -- 2 SIR for iid Data -- 3 SIR for Time Series Data -- 4 SIR for Spatial Data -- 5 Performance Evaluation of SSIR -- 6 Discussion -- References -- Model-Based Inverse Regression and Its Applications -- 1 Introduction -- 1.1 Model-Based Inverse Reduction -- 1.2 Sufficient Reduction in Applications -- 2 Inverse Reduction for Multivariate Count Data -- 2.1 Multinomial Inverse Regression in Text Analysis -- 2.2 Predictive Learning in Metagenomics via Inverse Regression -- 2.3 Poisson Graphical Inverse Regression -- 3 Inverse Reduction and Its Dual -- 3.1 Reduction via Principal Coordinate Analysis -- 3.2 A Supervised Inverse Regression Model -- 4 Adaptive Independence Test via Inverse Regression -- 5 Cook's Contributions on Model-Based Sufficient Reduction -- References -- Sufficient Dimension Folding with Categorical Predictors -- 1 Introduction -- 2 Review on Sufficient Dimension Folding -- 3 Sufficient Dimension Folding with Categorical Predictors -- 4 Estimation Methods -- 4.1 Individual Direction Ensemble Method -- 4.2 Least Squares Folding Approach (LSFA) -- 4.3 Objective Function Optimization Method -- 5 Estimation of Structural Dimensions -- 6 Numerical Analysis -- 6.1 Simulation Studies -- 6.1.1 Part I (Continuous Y, Forward Model) -- 6.1.2 Part II (Discrete Y, Inverse Model) -- 6.2 Application -- 7 Discussion -- 8 Appendix -- 8.1 Proofs -- 8.2 Additional Simulation and Data Analysis -- Three Histograms for the Real Data -- The Bootstrap Confidence Interval Plots for Real Data -- References -- Sufficient Dimension Reduction Through Independenceand Conditional Mean Independence Measures -- 1 Introduction -- 2 Estimating SY|X Through α-Distance Covariance -- 2.1 α-Distance Covariance -- 2.2 Estimation of the Central Space.
3 Estimating SE(Y|X) Through α-Martingale Difference Divergence -- 3.1 α-Martingale Difference Divergence -- 3.2 Estimation of the Central Mean Space -- 4 Simulation Studies -- 4.1 Model Setup -- 4.2 Comparisons of Estimating the Central Space -- 4.3 Comparisons of Estimating the Central Mean Space -- 5 Analysis of the Iris Data -- 6 Conclusion -- Appendix -- References -- Cook's Fisher Lectureship Revisited for Semi-supervised DataReduction -- 1 Introduction -- 2 Dimension Reduction by Isotonic Models -- 2.1 Construction of Isotonic Model -- 2.2 Maximum Likelihood Estimation of Γ -- 3 Numerical Examples -- 4 Real Data Example -- 5 Discussion -- References.
Record Nr. UNINA-9910484167603321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Festschrift in honor of R. Dennis Cook : fifty years of contribution to statistical science / / Efstathia Bura, Bing Li, editors
Festschrift in honor of R. Dennis Cook : fifty years of contribution to statistical science / / Efstathia Bura, Bing Li, editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (200 pages)
Disciplina 519.5
Soggetto topico Statistics
Mathematical statistics
Estadística matemàtica
Soggetto genere / forma Homenatges
Llibres electrònics
ISBN 3-030-69009-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Foreword -- A Tribute to Professor R. Dennis Cook -- Contents -- Using Mutual Information to Measure the Predictive Powerof Principal Components -- 1 Introduction -- 2 Overview of Previous Results -- 3 Conditional Mutual Information -- 3.1 Under the Linear Model -- 3.2 Beyond the Linear Regression Model -- 3.3 Beyond the Normal Distribution -- 4 Discussion -- References -- A Robust Estimation Approach for Mean-Shiftand Variance-Inflation Outliers -- 1 Introduction -- 2 Our Proposal and Some Background -- 2.1 A Generalized Setting -- 2.2 Some Technical Background -- 2.3 Our Proposal -- 2.4 Graphical Diagnostics -- 3 Simulation Study -- 4 Real-Data Examples -- 5 Final Remarks -- References -- Estimating Sufficient Dimension Reduction Spaces by Invariant Linear Operators -- 1 Introduction -- 2 Invariant Linear Operators -- 3 Invariant Linear Operator and Its Eigenvectors -- 4 Some Important Members of T Y|X -- 4.1 Sliced Average Variance Estimation -- 4.2 SIR-II -- 4.3 Contour Regression -- 4.4 Directional Regression -- 5 Two Estimation Methods Based on Invariant Operators -- 5.1 Iterative Invariant Transformations (IIT) -- 5.2 Nonparametrically Boosted Inverse Regression (NBIR) -- 6 Numerical Study -- 7 Concluding Remarks -- References -- Testing Model Utility for Single Index Models Under High Dimension -- 1 Introduction -- 2 Generalized SNR for Single Index Models -- 2.1 Notation -- 2.2 A Brief Review of the Sliced Inverse Regression (SIR) -- 2.3 Generalized Signal-to-Noise Ratio of Single Index Models -- 2.4 Global Testing for Single Index Models -- 3 The Optimal Test for Single Index Models -- 3.1 The Detection Boundary of Linear Regression -- 3.2 Single Index Models -- 3.3 Optimal Test for SIMa -- 3.4 Computationally Efficient Test -- 3.5 Practical Issues -- 4 Numerical Studies -- 5 Discussion -- Appendix: Proofs -- Assisting Lemmas.
Proof of Theorems -- References -- Sliced Inverse Regression for Spatial Data -- 1 Introduction -- 2 SIR for iid Data -- 3 SIR for Time Series Data -- 4 SIR for Spatial Data -- 5 Performance Evaluation of SSIR -- 6 Discussion -- References -- Model-Based Inverse Regression and Its Applications -- 1 Introduction -- 1.1 Model-Based Inverse Reduction -- 1.2 Sufficient Reduction in Applications -- 2 Inverse Reduction for Multivariate Count Data -- 2.1 Multinomial Inverse Regression in Text Analysis -- 2.2 Predictive Learning in Metagenomics via Inverse Regression -- 2.3 Poisson Graphical Inverse Regression -- 3 Inverse Reduction and Its Dual -- 3.1 Reduction via Principal Coordinate Analysis -- 3.2 A Supervised Inverse Regression Model -- 4 Adaptive Independence Test via Inverse Regression -- 5 Cook's Contributions on Model-Based Sufficient Reduction -- References -- Sufficient Dimension Folding with Categorical Predictors -- 1 Introduction -- 2 Review on Sufficient Dimension Folding -- 3 Sufficient Dimension Folding with Categorical Predictors -- 4 Estimation Methods -- 4.1 Individual Direction Ensemble Method -- 4.2 Least Squares Folding Approach (LSFA) -- 4.3 Objective Function Optimization Method -- 5 Estimation of Structural Dimensions -- 6 Numerical Analysis -- 6.1 Simulation Studies -- 6.1.1 Part I (Continuous Y, Forward Model) -- 6.1.2 Part II (Discrete Y, Inverse Model) -- 6.2 Application -- 7 Discussion -- 8 Appendix -- 8.1 Proofs -- 8.2 Additional Simulation and Data Analysis -- Three Histograms for the Real Data -- The Bootstrap Confidence Interval Plots for Real Data -- References -- Sufficient Dimension Reduction Through Independenceand Conditional Mean Independence Measures -- 1 Introduction -- 2 Estimating SY|X Through α-Distance Covariance -- 2.1 α-Distance Covariance -- 2.2 Estimation of the Central Space.
3 Estimating SE(Y|X) Through α-Martingale Difference Divergence -- 3.1 α-Martingale Difference Divergence -- 3.2 Estimation of the Central Mean Space -- 4 Simulation Studies -- 4.1 Model Setup -- 4.2 Comparisons of Estimating the Central Space -- 4.3 Comparisons of Estimating the Central Mean Space -- 5 Analysis of the Iris Data -- 6 Conclusion -- Appendix -- References -- Cook's Fisher Lectureship Revisited for Semi-supervised DataReduction -- 1 Introduction -- 2 Dimension Reduction by Isotonic Models -- 2.1 Construction of Isotonic Model -- 2.2 Maximum Likelihood Estimation of Γ -- 3 Numerical Examples -- 4 Real Data Example -- 5 Discussion -- References.
Record Nr. UNISA-996466399803316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui