This book shows the capabilities of Microsoft Excel in teaching environmental science statistics effectively. Similar to the previously published __Excel 2013 for Environmental Sciences Statistics__, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical environmental science problems. If understanding statistics isn’t the reader’s strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with.
Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in environmental science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, __Excel 2016 for Environmental Sciences Statistics: A Guide to Solving Practical Problems__ capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.
Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand environmental science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.

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zlib/Science (General)/Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton (auth.)/Excel 2016 for Environmental Sciences Statistics: A Guide to Solving Practical Problems_2803291.pdf

Quirk, Thomas J., Quirk, Meghan H., Horton, Howard F.

Adobe InDesign CC 2015 (Windows)

Springer Nature Switzerland AG

Springer London, Limited

Springer Nature (Textbooks & Major Reference Works), Cham, 2016

Place of publication not identified, 2016

Excel for statistics, Switzerland, 2016

Excel for statistics, Cham, 2016

Switzerland, Switzerland

1st ed. 2016, 2016

Aug 22, 2016

sm59958334

producers:
Adobe PDF Library 15.0

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Source title: Excel 2016 for Environmental Sciences Statistics: A Guide to Solving Practical Problems (Excel for Statistics)

Preface 8
Acknowledgements 12
Contents 14
Chapter 1: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 19
1.1 Mean 19
1.2 Standard Deviation 20
1.3 Standard Error of the Mean 21
1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 22
1.4.1 Using the Fill/Series/Columns Commands 22
1.4.2 Changing the Width of a Column 24
1.4.3 Centering Information in a Range of Cells 25
1.4.4 Naming a Range of Cells 26
1.4.5 Finding the Sample Size Using the=COUNT Function 28
1.4.6 Finding the Mean Score Using the=AVERAGE Function 28
1.4.7 Finding the Standard Deviation Using the=STDEV Function 28
1.4.8 Finding the Standard Error of the Mean 29
1.4.8.1 Formatting Numbers in Number Format (Two Decimal Places) 29
1.5 Saving a Spreadsheet 30
1.6 Printing a Spreadsheet 31
1.7 Formatting Numbers in Currency Format (Two Decimal Places) 33
1.8 Formatting Numbers in Number Format (Three Decimal Places) 35
1.9 End-of-Chapter Practice Problems 36
References 38
Chapter 2: Random Number Generator 39
2.1 Creating Frame Numbers for Generating Random Numbers 39
2.2 Creating Random Numbers in an Excel Worksheet 42
2.3 Sorting Frame Numbers into a Random Sequence 44
2.4 Printing an Excel File So That All of the Information Fits onto One Page 48
2.5 End-of-Chapter Practice Problems 51
Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing 53
3.1 Confidence Interval About the Mean 53
3.1.1 How to Estimate the Population Mean 53
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean 54
3.1.3 Estimating the Confidence Interval for the Chevy Impala in Miles Per Gallon 55
3.1.4 Where Did the Number ``1.96 ́ ́ Come From? 56
3.1.5 Finding the Value for t in the Confidence Interval Formula 57
3.1.6 Using Excel ́s TINV Function to Find the Confidence Interval About the Mean 58
3.1.7 Using Excel to Find the 95% Confidence Interval for a Car ́s mpg Claim 58
3.2 Hypothesis Testing 65
3.2.1 Hypotheses Always Refer to the Population of People, Plants, or Animals That You Are Studying 65
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis 66
3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used 67
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean 69
3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 69
3.2.3.2 STEP 2: Select the Appropriate Statistical Test 70
3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test 70
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,... 70
3.2.3.5 STEP 5: Decide on a Decision Rule 70
3.2.3.6 STEP 6: State the Result of Your Statistical Test 71
3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 71
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test 76
3.3.1 Different Ways to Accept the Null Hypothesis 76
3.3.2 Different Ways to Reject the Null Hypothesis 77
3.4 End-of-Chapter Practice Problems 77
References 81
Chapter 4: One-Group t-Test for the Mean 82
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test 82
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 83
4.1.2 STEP 2: Select the Appropriate Statistical Test 83
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test 83
4.1.3.1 Finding the Absolute Value of a Number 84
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test 84
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E 85
4.1.6 STEP 6: State the Result of Your Statistical Test 86
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 86
4.2 One-Group t-Test for the Mean 87
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? 93
4.4 End-of-Chapter Practice Problems 93
References 97
Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups 98
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test 99
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 99
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group 100
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test 101
5.1.4 STEP 4: Select the Appropriate Statistical Test 101
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test 102
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test 102
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E 102
5.1.7.1 Finding the Degrees of Freedom (df) for the Two-Group t-Test 103
5.1.8 STEP 8: State the Result of Your Statistical Test 103
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! 104
5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis 104
5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis 105
5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30 108
5.2.1 An Example of Formula #1 for the Two-Group t-Test 109
5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30 116
5.4 End-of-Chapter Practice Problems 123
References 126
Chapter 6: Correlation and Simple Linear Regression 127
6.1 What Is a ``Correlation? ́ ́ 127
6.1.1 Understanding the Formula for Computing a Correlation 132
6.1.2 Understanding the Nine Steps for Computing a Correlation, r 132
6.2 Using Excel to Compute a Correlation Between Two Variables 134
6.3 Creating a Chart and Drawing the Regression Line onto the Chart 139
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points 141
6.3.1.1 Drawing the Regression Line Through the Data Points on the Chart 145
6.3.1.2 Moving the Chart Below the Table in the Spreadsheet 147
6.3.1.3 Making the Chart ``Longer ́ ́ So That It Is ``Taller ́ ́ 148
6.3.1.4 Making the Chart ``Wider ́ ́ 148
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page 149
6.5 Finding the Regression Equation 151
6.5.1 Installing the Data Analysis ToolPak into Excel 152
6.5.1.1 Installing the Data Analysis ToolPak into Excel 2016 152
6.5.1.2 Installing the Data Analysis ToolPak into Excel 2013 153
6.5.1.3 Installing the Data Analysis ToolPak into Excel 2010 154
6.5.1.4 Installing the Data Analysis ToolPak into Excel 2007 154
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression 155
6.5.2.1 Finding the y-Intercept, a, of the Regression Line 159
6.5.2.2 Finding the Slope, b, of the Regression Line 159
6.5.3 Finding the Equation for the Regression Line 159
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value 160
6.6 Adding the Regression Equation to the Chart 161
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table 164
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet 164
6.8.1 Printing Only the Table and the Chart on a Separate Page 165
6.8.2 Printing Only the Chart on a Separate Page 165
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page 166
6.9 End-of-Chapter Practice Problems 166
References 171
Chapter 7: Multiple Correlation and Multiple Regression 173
7.1 Multiple Regression Equation 173
7.2 Finding the Multiple Correlation and the Multiple Regression Equation 176
7.3 Using the Regression Equation to Predict FRUIT PRODUCED 181
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression 181
7.5 End-of-Chapter Practice Problems 185
References 190
Chapter 8: One-Way Analysis of Variance (ANOVA) 191
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) 193
8.2 How to Interpret the ANOVA Table Correctly 196
8.3 Using the Decision Rule for the ANOVA F-Test 196
8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test 197
8.4.1 Comparing COMPACTS vs. LARGE in Highway mpg Using the ANOVA t-Test 198
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test 199
8.4.1.2 Stating the Decision Rule for the ANOVA t-Test 200
8.4.1.3 Performing an ANOVA t-Test Using Excel Commands 200
8.5 End-of-Chapter Practice Problems 202
References 207
Appendices 208
Appendix A: Answers to End-of-Chapter Practice Problems 208
Appendix B: Practice Test 241
Appendix C: Answers to Practice Test 252
Appendix D: Statistical Formulas 263
Appendix E: t-Table 265
Index 266

This book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical environmental science problems. If understanding statistics isn?t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel is an effective learning tool for quantitative analyses in environmental science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Environmental Science Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel 2016 to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand environmental science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. Includes 165 illustrations in color Suitable for undergraduates or graduate students Prof. Tom Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He is Professor of Marketing in the Walker School of Business & Technology at Webster University in St. Louis, Missouri (USA). He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph. D. in Educational Psychology from Stanford University, and an MBA from The University of Missouri-St. Louis. Dr. Meghan Quirk holds a Ph. D. in Biological Education and an M.A. in Biological Sciences from the University of Northern Colorado (UNC) and a B.A. in Biology and Religion at Principia College in Elsah, Illinois. She has co-authored an article on shortgrass steppe ecosystems in Photochemistry & Photobiology. She was a National Science Foundation Fellow GK-12, and currently teaches science in Bailey, Colorado. Howard F. Horton holds an MS in Biological Sciences from the University of Northern Colorado (UNC) and a BS in Biological Sciences from Mesa State College. He has worked on research projects in Pawnee National Grasslands and Long-Term Ecological Research at Toolik Lake, Alaska. He has co-authored articles in The International Journal of Speleology and The Journal of Cave and Karst Studies. He was a National Science Foundation Fellow GK-12. He is currently the Angler Outreach Coordinator with Colorado Parks and Wildlife

Front Matter....Pages i-xvii
Sample Size, Mean, Standard Deviation, and Standard Error of the Mean....Pages 1-20
Random Number Generator....Pages 21-34
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing....Pages 35-63
One-Group t-Test for the Mean....Pages 65-80
Two-Group t-Test of the Difference of the Means for Independent Groups....Pages 81-109
Correlation and Simple Linear Regression....Pages 111-156
Multiple Correlation and Multiple Regression....Pages 157-174
One-Way Analysis of Variance (ANOVA)....Pages 175-191
Back Matter....Pages 193-252

2016-11-20