Scientific Research Methodologies Syllabus - Copy.pptx

Scientific Research Methodologies Syllabus ppt

1. Scientific Research Methodologies Syllabus

2. Data Analysis: Descriptive and inferential statistics. Statistical software and data analysis techniques. Data visualization and interpretation.

3. Descriptive and Inferential Statistics: Essentially, descriptive statistics state facts and proven outcomes from a population, whereas inferential statistics analyze samplings to make predictions about larger populations. Descriptive Statistics: Summarize and describe data. Measures include mean, median, mode, range, and standard deviation. Graphical representations (histograms, box plots) help visualize data. Inferential Statistics: Make inferences about populations based on sample data. Techniques include hypothesis testing, confidence intervals, and regression analysis.

4. Statistical software and data analysis techniques: R: A powerful open-source statistical programming language. Widely used for data manipulation, visualization, and modelling. Python: Popular for data analysis and machine learning. Libraries like Pandas, NumPy, and Matplotlib are essential. SPSS (Statistical Package for the Social Sciences): Widely used in social sciences and business research. Provides a user-friendly interface. Excel: Basic statistical functions are available. Suitable for small-scale analyses.

5. Data visualization and interpretation : Data visualization is the process of putting data into a chart, graph, or other visual format that helps inform analysis and interpretation . The importance of data visualization is simple:  it helps people see, interact with, and better understand data . Most Common Types of Data Visualization : Column Chart. Pie Chart. Bar Chart. Heat Maps. Scatter Plot. Bubble Chart. Funnel Chart.