{"product_id":"140973","title":"Quantitative research methods and statistical analysis using R ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/WQtVEhnoezAZlxg2LpjJep.png?v=1764956774\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n\u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003e Quantitative research methods and statistical analysis using R \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/125231532\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cdiv\u003e SPSS is convenient to use because analysis can be performed simply by clicking on the menu, but because it is a commercial program, there were cases where accessibility issues occurred.\u003cbr\u003e There is also the inconvenience of not being able to immediately update the latest analysis techniques.\u003cbr\u003e \u003cbr\u003eThis book was written in response to requests to add examples using Python and R, which are free programs that can implement the latest analysis techniques, to statistical analysis books.\u003cbr\u003e R is being made more user-friendly with a Windows-based program called RStudio.\u003cbr\u003e\u003cbr\u003e This book covers the basics of quantitative research and statistical analysis, from t-tests, regression analysis, ANOVA, ANCOVA, repeated-measures ANOVA, categorical data analysis, and nonparametric tests, and provides detailed examples of analysis using R (RStudio).\u003cbr\u003e\n\n\u003c\/div\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e preface\u003cbr\u003e\u003cbr\u003e \u003cb\u003eIntroduction R Foundation\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1. RStudio Structure\u003cbr\u003e 1) R package\u003cbr\u003e 2) Four windows of RStudio\u003cbr\u003e 2. RStudio Basics I\u003cbr\u003e 1) Install and update R and RStudio\u003cbr\u003e 2) Specify the working directory\u003cbr\u003e 3) R data types and features\u003cbr\u003e 3. RStudio Basics II\u003cbr\u003e 1) Creating and saving R objects\u003cbr\u003e 2) Dataframe\u003cbr\u003e 3) Others\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 1: Fundamentals of Quantitative Research\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Variables and Scales\u003cbr\u003e 1) Types of variables\u003cbr\u003e 2) Type of scale\u003cbr\u003e 2.\u003cbr\u003e Sampling method\u003cbr\u003e 1) Probabilistic sampling\u003cbr\u003e 2) Non-probability sampling\u003cbr\u003e 3. \u003cbr\u003eDescriptive and inferential statistics\u003cbr\u003e 1) Statistics and probability theory\u003cbr\u003e 2) Differences between descriptive and inferential statistics\u003cbr\u003e 3) Descriptive statistics\u003cbr\u003e 4.\u003cbr\u003e R example\u003cbr\u003e 1) Data entry and frequency analysis\u003cbr\u003e 2) Central tendency values ​​and dispersion\u003cbr\u003e 3) Descriptive statistics by group\u003cbr\u003e 4) Interquartile deviation and box plot\u003cbr\u003e 5) Standard score\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 2: Experimental Design and Validity Threats\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Experimental design and internal validity threats\u003cbr\u003e 1) Experimental design and causal inference\u003cbr\u003e 2) Random sampling and random assignment, true experimental design and quasi-experimental design\u003cbr\u003e 3) Threats to internal validity\u003cbr\u003e 4) Quasi-experimental design and threats to internal validity\u003cbr\u003e 2.\u003cbr\u003e Threats to external validity and construct validity\u003cbr\u003e 1) Threats to external validity\u003cbr\u003e 2) Threat factors to recruitment validity\u003cbr\u003e 3.\u003cbr\u003e Relationships between internal, external, and construct validity threats\u003cbr\u003e 1) Relationship between internal validity and external validity\u003cbr\u003e 2) Relationship between internal validity and recruiting validity\u003cbr\u003e 3) Relationship between internal validity and external validity\u003cbr\u003e 4.\u003cbr\u003e Advanced experimental design\u003cbr\u003e 1) Forward-looking design and retrospective design\u003cbr\u003e 2) Propensity score matching\u003cbr\u003e 3) Causal inference and experimental design considerations\u003cbr\u003e · Practice problems\u003cbr\u003e \u003cbr\u003e\u003cb\u003eChapter 3: Fundamentals of Statistical Analysis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Statistical hypothesis testing\u003cbr\u003e 1) Principles of statistical hypothesis testing\u003cbr\u003e 2) Null and alternative hypotheses in two-sided\/one-sided tests\u003cbr\u003e 3) Type I error, Type II error, confidence interval, power\u003cbr\u003e 4) Criticism of statistical hypothesis testing\u003cbr\u003e 2.\u003cbr\u003e random variable\u003cbr\u003e 1) Characteristics of random variables\u003cbr\u003e 2) Expected value and variance\u003cbr\u003e 3.\u003cbr\u003e Central limit theorem\u003cbr\u003e 1) Distribution of sample consensus\u003cbr\u003e 2) Distribution of sample means\u003cbr\u003e 4.\u003cbr\u003e Basic probability distribution\u003cbr\u003e 1) Normal distribution\u003cbr\u003e 2) Binomial distribution\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 4 Z-test and t-test\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Inference statistics\u003cbr\u003e 1) Point estimation and interval estimation\u003cbr\u003e 2) Significance level, significance probability, rejection threshold, statistical power\u003cbr\u003e 2.\u003cbr\u003e single-sample test\u003cbr\u003e 1) Hypothesis testing for variables following the Z-distribution: Z-test\u003cbr\u003e 2) Hypothesis testing for variables following a t-distribution: t-test\u003cbr\u003e 3) Statistical power\u003cbr\u003e 4) R Example: One-Sample t-Test\u003cbr\u003e 3.\u003cbr\u003e independent sample test\u003cbr\u003e 1) When the population variance is known or the central limit theorem can be used: Z-test\u003cbr\u003e 2) When the parent variance is unknown but homoscedasticity is assumed: t-test \u003cbr\u003e3) When the parent variance is unknown and homoscedasticity cannot be assumed: Welch-Aspin test\u003cbr\u003e 4) R Example: Independent Samples t-Test\u003cbr\u003e 4.\u003cbr\u003e Paired sample test\u003cbr\u003e 1) Statistical model and assumptions\u003cbr\u003e 2) R Example: Paired Samples t-Test\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 5 Correlation Analysis and Reliability\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Correlation analysis\u003cbr\u003e 1) Covariance\u003cbr\u003e 2) Correlation coefficient\u003cbr\u003e 3) Statistical assumptions and testing of the Pearson correlation coefficient\u003cbr\u003e 4) Partial correlation coefficient and partial correlation coefficient\u003cbr\u003e 5) R example\u003cbr\u003e 2.\u003cbr\u003e Reliability\u003cbr\u003e 1) Statistical assumptions and formulas\u003cbr\u003e 2) Reliability calculation method\u003cbr\u003e 3) Standard error of measurement\u003cbr\u003e 4) Factors affecting reliability\u003cbr\u003e 5) R example\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 6 Regression Analysis I: Simple Regression Analysis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Statistical models and assumptions\u003cbr\u003e 2.\u003cbr\u003e Checking Statistical Assumptions: Residual Analysis\u003cbr\u003e 1) Independence\u003cbr\u003e 2) Regularity\u003cbr\u003e 3) Equal variance\u003cbr\u003e 3.\u003cbr\u003e Hypothesis testing\u003cbr\u003e 1) Significance test of regression coefficients\u003cbr\u003e 2) Sum of squares decomposition and F-test\u003cbr\u003e 3) Coefficient of determination\u003cbr\u003e 4.\u003cbr\u003e Diagnosing Regression Models\u003cbr\u003e 5.\u003cbr\u003e R example\u003cbr\u003e 1) Pre- and post-tests of the experimental and control groups\u003cbr\u003e 2) School grades and college entrance exam scores\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 7 Regression Analysis II: Multiple Regression Analysis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1. \u003cbr\u003eStatistical models and assumptions\u003cbr\u003e 2.\u003cbr\u003e Hypothesis testing\u003cbr\u003e 1) Sum of squares decomposition and F-test\u003cbr\u003e 2) Model parsimony and modified coefficient of determination\u003cbr\u003e 3.\u003cbr\u003e Variable selection and multicollinearity\u003cbr\u003e 1) Variable selection\u003cbr\u003e 2) Multicollinearity\u003cbr\u003e 4.\u003cbr\u003e Other Key Concepts\u003cbr\u003e 1) Create dummy variables\u003cbr\u003e 2) Standardization coefficient\u003cbr\u003e 3) Centralization\u003cbr\u003e 5.\u003cbr\u003e R example\u003cbr\u003e 1) CSAT Korean language section score\u003cbr\u003e 2) Cyber ​​flight experience\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 8 ANOVA I: One-Way ANOVA\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Statistical models and assumptions\u003cbr\u003e 2.\u003cbr\u003e Hypothesis testing\u003cbr\u003e 1) Checking statistical assumptions: Residual analysis\u003cbr\u003e 2) Sum of squares decomposition and F-test\u003cbr\u003e 3.\u003cbr\u003e Contrast and post-comparison\u003cbr\u003e 1) Contrast\u003cbr\u003e 2) Post-comparison\u003cbr\u003e 4.\u003cbr\u003e Other Key Concepts\u003cbr\u003e 1) Variables and levels\u003cbr\u003e 2) Multiple testing error\u003cbr\u003e 3) Effect size\u003cbr\u003e 5.\u003cbr\u003e R example\u003cbr\u003e 1) When the assumption of equal variance is met\u003cbr\u003e 2) When the assumption of equal variance is not met\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 9 ANOVA II: Two-Way ANOVA\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Statistical models and assumptions\u003cbr\u003e 2.\u003cbr\u003e Hypothesis testing\u003cbr\u003e 1) Checking statistical assumptions: Residual analysis\u003cbr\u003e 2) Sum of squares decomposition and F-test\u003cbr\u003e 3.\u003cbr\u003e Main effects and interaction effects\u003cbr\u003e 1) Main effect\u003cbr\u003e 2) When there is no interaction effect \u003cbr\u003e3) When there is an interaction effect\u003cbr\u003e 4.\u003cbr\u003e Example of interaction effects\u003cbr\u003e 1) If there is no interaction effect\u003cbr\u003e 2) When there is an interaction effect\u003cbr\u003e 5.\u003cbr\u003e R example\u003cbr\u003e 1) When the interaction effect is not significant: Private education and math grades\u003cbr\u003e 2) If the interaction effect is significant: Rope jumping record\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 10 ANCOVA (Analysis of Covariance)\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Statistical models and assumptions\u003cbr\u003e 1) Statistical model\u003cbr\u003e 2) Statistical assumptions\u003cbr\u003e 2.\u003cbr\u003e Hypothesis testing\u003cbr\u003e 3.\u003cbr\u003e Key Concepts\u003cbr\u003e 1) Covariates\u003cbr\u003e 2) EMM\u003cbr\u003e 3) ANCOVA effect size\u003cbr\u003e 4. Things to keep in mind when conducting ANCOVA studies\u003cbr\u003e 1) ANCOVA and homogeneous groups\u003cbr\u003e 2) t-test on pre-test scores\u003cbr\u003e 3) ANCOVA when there is a large difference in pre-test scores between groups\u003cbr\u003e 4) ANCOVA and sample size by group\u003cbr\u003e 5) Mixing of experimental treatments and experimental units\u003cbr\u003e 5.\u003cbr\u003e R example\u003cbr\u003e 1) Pre- and post-test\u003cbr\u003e 2) Academic enthusiasm by department\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 11 rANOVA (Repeated Measures Analysis of Variance)\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Essential Terminology\u003cbr\u003e 1) Intrinsic design vs. cross-design\u003cbr\u003e 2) Wireless effect vs. fixed effect\u003cbr\u003e 3) Section\u003cbr\u003e 2.\u003cbr\u003e Statistical models and assumptions\u003cbr\u003e 1) Experimental design features\u003cbr\u003e 2) Statistical model \u003cbr\u003e3) Statistical assumptions\u003cbr\u003e 3.\u003cbr\u003e Hypothesis testing, sum of squares decomposition, F-test\u003cbr\u003e 4.\u003cbr\u003e caution\u003cbr\u003e 1) ANCOVA vs. rANOVA\u003cbr\u003e 2) Advantages and limitations of rANOVA\u003cbr\u003e 5.\u003cbr\u003e R example\u003cbr\u003e 1) Repeated measurement data and data format\u003cbr\u003e 2) Pre- and post-test\u003cbr\u003e 3) Pre-, post-, and follow-up inspections\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 12 Categorical Data Analysis (Chi-Square Test)\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e Cross-tabulation\u003cbr\u003e 1) Joint probability, marginal probability, conditional probability\u003cbr\u003e 2) Independence test\u003cbr\u003e 3) Black statistics and statistical assumptions\u003cbr\u003e 4) Ozbi\u003cbr\u003e 5) R example\u003cbr\u003e 2.\u003cbr\u003e Logistic regression model\u003cbr\u003e 1) Statistical model\u003cbr\u003e 2) Statistical assumptions\u003cbr\u003e 3) R example\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 13 Nonparametric Tests\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.\u003cbr\u003e independent sample test\u003cbr\u003e 2.\u003cbr\u003e Paired sample test\u003cbr\u003e 1) Two groups\u003cbr\u003e 2) Two or more groups\u003cbr\u003e 3.\u003cbr\u003e R example\u003cbr\u003e 1) Independent sample test\u003cbr\u003e 2) Paired sample test\u003cbr\u003e · Practice problems\u003cbr\u003e\u003cbr\u003e Practice Problem Answers and Solutions\u003cbr\u003e\u003cbr\u003e Appendix 493\u003cbr\u003e 〈Appendix 1〉 Distribution Table (Z-distribution, t-distribution, F-distribution, chi-square distribution)\u003cbr\u003e Appendix 2: Classification Criteria for US WWC Papers\u003cbr\u003e Appendix 3: APA Citation Format Rules and Examples\u003cbr\u003e\u003cbr\u003e R, analysis data, tables, figures, and in-depth\u003cbr\u003e References\u003cbr\u003e Search \u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS\u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n \u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e- \u003cstrong\u003eDate of issue:\u003c\/strong\u003e March 3, 2024\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 541 pages | 1,088g | 188*255*35mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9788999730597\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN10:\u003c\/strong\u003e 899973059X \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43894421454890,"sku":"140973","price":46.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/9f1c709203af8cc1842560e7ab79e6ff.jpg?v=1765433011","url":"https:\/\/librairie.coreenne.fr\/en\/products\/140973","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}