(Tiểu luận) mid term report topic research and perform basic statistics and data analysis in spss software

FOREIGN TRADE UNIVERSITY FACULTY OF BANKING AND FINANCE 000 MID-TERM REPORT TOPIC: RESEARCH AND PERFORM BASIC STATISTICS AND DATA ANALYSIS IN SPSS SOFTWARE Subject: Quantitative Methods Class: TCHE442(HK1-2324)1.2 Teacher: Dr Nguyễn Đình Đạt Group: No Member Student ID Phan Thị Như Anh 2112340008 Nguyễn Thu Giang 2112340024 Đào Hương Giang 2112340023 Vũ Phương Anh 2112340010 Hoàng Ngọc Linh 2114310053 TABLE OF CONTENT Overview of SPSS Software for Data Analysis Descriptive Statistics a Distribution and central tendencies ● The purpose of distribution and central tendencies ● Using an example dataset to demonstrate how to perform distribution and central tendencies in SPSS ● Results b Association table 12 ● The purpose of Association table 12 ● Using an example dataset to demonstrate how to perform Association table in SPSS 12 ● Results 14 Testing the Reliability of the Research Scale Using Cronbach's Alpha 16 3.1 Cronbach’s Alpha reliability testing 16 3.2 Using an example dataset to demonstrate how to perform in reliability of the Research Scale SPSS 17 3.3 Results 18 Exploratory factor analysis 19 4.1 Overview of exploratory factor analysis (EFA) 19 4.2 Use an example dataset to demonstrate how to perform exploratory factor analysis (EFA) 20 4.3 Results 22 Correlational analysis 25 5.1 Overview of correlational analysis 25 5.2 Use an example dataset to demonstrate how to perform correlation analysis 25 5.3 Results 27 Regression analysis & Analysis of Variance (ANOVA) 27 6.1 Overview of regression analysis 27 6.2 Overview of Analysis of Variance (ANOVA) 28 6.3 Use an example dataset to demonstrate how to perform Regression analysis & Analysis of Variance in SPSS .29 6.4 Results 30 Mean comparison of two groups using a t-test 33 7.1 The purpose of a t-test 33 7.2 Use an example dataset to demonstrate how to perform a t-test in SPSS 33 7.3 Results 35 Logistic regression 37 8.1 The purpose of logistic regression 37 8.2 Use an example dataset to demonstrate how to perform logistic regression in SPSS 38 8.3 Results 40 Overview of SPSS Software for Data Analysis SPSS (Statistical Package for the Social Sciences) is a software package widely used for statistical analysis and data management It provides a comprehensive range of tools and techniques for analyzing and manipulating data, making it popular among researchers, data analysts, and social scientists SPSS offers a user-friendly graphical interface that allows users to perform various statistical analyses and generate reports without requiring extensive programming knowledge It supports both basic and advanced statistical procedures, including descriptive statistics, hypothesis testing, regression analysis, factor analysis, cluster analysis, and more These features make it suitable for a wide range of research fields, including social sciences, market research, healthcare, and business analytics key features of SPSS include: - Data Management: SPSS allows users to import, clean, and manipulate data easily It provides tools for data screening, variable transformation, recoding, merging datasets, and handling missing values - Statistical Analysis: SPSS provides a wide range of statistical procedures to analyze data Users can perform descriptive statistics, t-tests, ANOVA, chi-square tests, correlation analysis, regression analysis, and many other statistical tests - Data Visualization: SPSS offers various tools for data visualization, including charts, graphs, and plots Users can create bar charts, scatter plots, histograms, and more to visually explore and present their data - Customizability: SPSS allows users to customize their analyses and outputs according to their specific research needs It provides options to modify variable labels, value labels, and define custom functions and transformations - Output and Reporting: SPSS generates comprehensive output files that include statistical results, tables, and charts The output can be exported to different formats, such as Microsoft Excel or PDF, for further analysis or reporting purposes - Integration with Other Software: SPSS integrates well with other software packages, allowing users to import and export data from various formats It also supports syntax programming, enabling advanced users to automate analyses and generate reproducible workflows Descriptive Statistics Descriptive statistics is a branch of statistics that focuses on summarizing and describing the main characteristics of a dataset It provides a way to organize, analyze, and present data in a meaningful and concise manner Descriptive statistics techniques are used to describe the central tendency, variability, and distribution of a dataset The most commonly used measures of central tendency are the mean (average), median (middle value), and mode (most frequently occurring value) These measures provide insight into the typical value around which the data points tend to cluster a Distribution and central tendencies ● The purpose of distribution and central tendencies The purpose of analyzing distribution and central tendencies in a dataset is to gain an understanding of the overall characteristics and patterns of the data These statistical measures provide valuable information about the typical values, spread, and shape of the data, allowing researchers and analysts to summarize and interpret the dataset effectively Distribution helps to understand how the data is spread out across different values or intervals It provides insights into the frequency or occurrence of different values and the shape of the data Common methods used to analyze distribution include histograms, frequency tables, and probability distributions Understanding the distribution can help identify outliers, assess the skewness or symmetry of the data, and guide further analysis and decision-making Measures of central tendency provide information about the typical or central value around which the data points tend to cluster The three commonly used measures of central tendency are the mean, median, and mode - Mean: The mean is the average value and is calculated by summing all the data points and dividing by the total number of observations It represents the arithmetic center of the data and is sensitive to extreme values or outliers - Median: The median is the middle value when the data is ordered from lowest to highest It separates the data into two equal halves and is not affected by extreme values It is a robust measure of central tendency - Mode: The mode is the value that appears most frequently in the dataset It represents the peak or most common value A dataset can have one mode (unimodal), two modes (bimodal), or more (multimodal) Analyzing central tendencies helps in understanding where the majority of the data points lie and provides a reference point to compare individual observations It aids in summarizing the data in a single representative value and facilitates comparisons between different groups or datasets Document continues below Discover more from: Phương pháp lượng tài hmu234 Trường Đại học… 22 documents Go to course Sóng-2 - Phân tích Sóng - Xn Quỳnh Phương 100% (1) ● Using an example dataset to demonstrate how to perform distribution pháp… and central tendencies in SPSS Step 1: Choose the "Analyze" menu and select Descriptive Statistics, Frequencies option 3 - ghi thuế ghi thuếvở ghi thuếvở… Phương pháp lượng tài… None ghi thuếvở ghi thuếvở ghi thuếvở… Phương pháp lượng tài… None Phương pháp None Step 2: When the Frequencies tab appears, pick Age, Annual 3income, Work hours a week lượng tài… and Overall job satisfaction to the Variable(s) column, then choose Statistics Mkt-cb - Summary 43 67 Ggz en… Phương pháp lượng tài… None Lecture Notes note Phương pháp lượng tài… None Step 3: In Percentile Values, choose Quartiles; in Central Tendency, choose Mean, Median; in Dispersion, choose Std deviation, Variance and in distribution, choose Skewness and Kurtosis Step 4: We can also add charts into the output document by opening Charts and selecting Histogram with a normal curve