Stat

• Statistics is the systematic way of collecting, organizing, summarizing, and analyzing information to draw conclusions, answer questions, or predict logical possible outcomes. In addition, statistics is about providing a measure of confidence in any conclusions.
• Statistics can be considered as numerical statements of facts which are highly convenient and meaningful forms of communication. The subjects of statistics, as it seems, is not a new discipline but it is as old as the human society itself.
• The word statistics is derived from the Latin word /statis/ which means a political state or government. It was originally applied in connection with kings and monarchs collecting data on their citizenry which pertained to state wealth, taxes collected population and so on.
• The scope of statistics in the ancient times was primarily limited to the collection of demographic, property and wealth data of a country by governments for framing military and fiscal policies.
• Statistics' usefulness has now spread to diverse fields such as agriculture, accounting, marketing, economics, management, medicine, political science, psychology, sociology, engineering, journal, metrology, tourism, etc. And hence, statistics is included in the curriculum of many professional and academic study programs.
• John Naisbitt: 'We are drowning in information but starved in knowledge'
• Clifford Stoll: 'Data is not information, information is not knowledge, knowledge is not understanding, understanding is not wisdom'
• Conducting research on an entire population is often difficult and expensive, so we typically look at a sample
• The step of looking at a sample is vital to the statistical process because if the data are not collected correctly, the conclusions drawn are meaningless
• Do not overlook the importance of appropriate data collection
• PROCESS OF STATISTICS: Organize and summarize the information

  Descriptive statistics allow the researcher to obtain an overview of the data and can help determine the type of statistical methods the researcher should use
• PROCESS OF STATISTICS: Draw conclusion from the information

  In this step, the information collected from the sample is generalized to the population. Inferential statistics use methods that take results obtained from a sample, extend them to the population, and measure the reliability of the result
• Why Study Statistics? Weighing in the benefits of number-crunching
• In an era where data, information, and news can easily be shared, our generation is now more open and eager to do research in all fields of studies and jobs
• Limitations of Statistics: Knowing the boundaries of what it can do
• Limitations of Statistics

  • Statistics is not suitable to the study of qualitative phenomenon
  • Statistics does not study individuals
  • Statistical laws are not exact
  • Statistical results can be misused
  • Statistics is only one of the methods of studying a problem
• Statistics is ill-suited for the study of qualitative phenomena, as it primarily deals with quantitative data
• Statistics focuses on groups and aggregates, often overlooking individual variations
• Statistical laws are probabilistic rather than absolute, meaning they provide likelihoods rather than certainties
• Statistical results such as tables, graphs, and statements can be misused or misinterpreted, leading to incorrect conclusions
• While valuable, statistics is just one tool among various methods for studying problems. Relying solely on statistical analysis may overlook qualitative insights, historical context, or other important factors
• Statistics is only one of the methods of studying a problem. Relying solely on statistical analysis may overlook qualitative insights, historical context, or other important factors necessary for a comprehensive understanding of a given issue
• Descriptive and Inferential Statistics
• Descriptive Statistics


  Organizing and summarizing data. Descriptive statistics describe data through numerical summaries, tables, and graphs. It is concerned with summary calculations, graphs, charts, and tables to describe the data
• Descriptive Statistics


  Deals with describing data without attempting to infer anything that goes beyond the given set of data. It consists of collection, organization, summarization, and presentation of data in a convenient and informative way
• Inferential Statistics


  Uses methods that take a result from a sample, extend it to the population, and measure the reliability of the result. It includes the methods used to find out something about a population based on a sample. Inferential statistics utilizes sample data to make decisions for the entire data set
• Inferential Statistics

  Descriptive statistics is linked with probability theory so that an investigator can generalize the results of a study. Inferential statistics is important because statistical data usually arises from a sample
• Statistics can be grouped as

  Descriptive and Inferential
• Examples of Descriptive Statistics

  • Frequency Distribution
  • Measures of Central Tendency
  • Measures of Dispersion
  • Normal Distribution
• Examples of Inferential Statistics

  • Pearson Product Moment Correlation Coefficient
  • T-test
  • Chi-square
• Parametric Tests

  • Independent Samples t-test
  • Paired Samples t-test
  • F-test
  • Pearson’s r
  • Simple Linear and Multiple Regression Analyses
• Non-Parametric Tests

  • Chi-square tests
  • McNemar Test and Cochran’s Q test
  • Wilcoxon Test, Mann Whitney U Test
  • Kruskal-Walllis and Friedman’s ANOVA
  • Spearman’s Rho