Название: Simplifying Statistics for Graduate Students: Making the Use of Data Simple and User-Friendly Автор: Susan Rovezzi Carroll, David J. Carroll Издательство: Rowman & Littlefield Publishers Год: 2023 Страниц: 135 Язык: английский Формат: pdf (true), epub Размер: 10.2 MB
One of the greatest barriers to completing a graduate thesis or a doctoral dissertation is statistics. Oftentimes, the journey through graduate school is gratifying when the content courses in the chosen field of study are undertaken. Conversely, the statistics courses are met with trepidation. Many graduate students feel lost when it comes to dealing with data. Simplifying Statistics for Grad Students:Making the Use of Data Simple and User-Friendly is intended to help graduate students move through the barriers that seem formidable but are not. While this book is not a statistics text and does not purport to be such, it introduces graduate students to basic statistical concepts in an easy-to-comprehend manner. It is also a handbook that they can refer back to time and time again. Expertise with data is expected of graduate students. Simplifying Statistics for Grad Students is an antidote for the research and statistics blues.
One of the greatest barriers to completing a graduate thesis or a doctoral dissertation is research that includes statistics. Oftentimes, the journey through graduate school is gratifying when the content courses in the chosen field of study are undertaken. Conversely, the courses in research methods and statistics are met with trepidation and anxiety. Many graduate students feel lost when it comes to dealing with data. Some students even quit at the end of their programs, which is why ABD (all but dissertation) applies to many PhDs.
This book is intended to help you move through the barriers that seem formidable but are not. This is not a statistics text and does not purport to be such. Rather, it is a way to introduce you to basic statistical concepts in a gentle, easy-to-comprehend manner so that you can become the success that you set out to be when you signed on to your academic journey.
Chapter 1 presents the concept of variables: What are they and how do you measure them? Knowing the differences in measurement scales, selecting the correct measurement scales for variables, and identifying which ones you use for different statistical procedures are significant steps in setting up data. This understanding is vital; the use of statistical procedures depends on this basic knowledge.
Next, chapter 2 discusses the steps needed to manage data sets. Often-times, the steps are bypassed allowing for errors and misinformation to emerge from data sets. Taking the time to develop frequency distributions and more importantly, examining them in detail, are some of the most valuable steps in data management.
Chapter 3 presents graphing techniques that are most beneficial to graduate students’ research. Correctly choosing and then setting up graphs are discussed in this chapter along with some mistakes to avoid. Graphing can be an asset in the ability for graduate students to communicate their results in a simple, informative manner.
Chapter 4 begins the statistics presentation with descriptive statistics. The mean, median, and mode are used often every day. This chapter explains the three measures and when to use each one. Chapter 5 is a complement as it takes chapter 4 and explains why variability is critical as a partner to descriptive statistics. The benefit of understanding, and then using, the normal curve and percentiles is discussed in this chapter...
• Introduction • Chapter 1 Variables and How to Measure Them • Chapter 2 Intelligently Managing Your Data • Chapter 3 Graphing Techniques to Support Your Data • Chapter 4 Means, Medians, and Modes and When to Use Each • Chapter 5 Measuring Variability: An Important Role in Data • Chapter 6 Random Sampling and Other Useful Sampling Strategies • Chapter 7 Stating Hypotheses and Hypothesis Testing • Chapter 8 t-Test Procedures • Chapter 9 ANOVA Procedures • Chapter 10 Chi-Square Procedures • Chapter 11 Correlation Procedures • Chapter 12 Regression Procedures • Chapter 13 Practical Tips for Graduate Students • About the Authors
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