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statistics PGDM.pptx
- 1. SUBJECT: Quantitative techniques Topic: statistics Presented by: Shirisha R Assistant professor Regional college of management Bangalore
- 2. Introduction to statistics: Statistics is a mathematical body of science that pertains to the collection, analysis, interpretation or explanation, and presentation of data, or as a branch of mathematics. Some consider statistics to be a distinct mathematical science rather than a branch of mathematics. While many scientific investigations make use of data, statistics is concerned with the use of data in the context of uncertainty and decision making in the face of uncertainty. In applying statistics to a problem, it is common practice to start with a population or process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Ideally, statisticians compile data about the entire population (an operation called census). This may be organized by governmental statistical institutes. Descriptive statistics can be used to summarize the population data. Numerical descriptors include mean and standard deviation for continuous data (like income), while frequency and percentage are more useful in terms of describing categorical data (like education).
- 3. When a census is not feasible, a chosen subset of the population called a sample is studied. Once a sample that is representative of the population is determined, data is collected for the sample members in an observational or experimental setting. Again, descriptive statistics can be used to summarize the sample data. However, drawing the sample contains an element of randomness; hence, the numerical descriptors from the sample are also prone to uncertainty. To draw meaningful conclusions about the entire population, inferential statistics is needed. It uses patterns in the sample data to draw inferences about the population represented while accounting for randomness. These inferences may take the form of answering yes/no questions about the data (hypothesis testing), estimating numerical characteristics of the data (estimation), describing associations within the data (correlation), and modeling relationships within the data (for example, using regression analysis). Inference can extend to forecasting, prediction, and estimation of unobserved values either in or associated with the population being studied. It can include extrapolation and interpolation of time series or spatial data, and data mining.
- 4. MEANING OF STATISTICS: Statistical is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. DEFINITION OF STATISTICS: “statistics are numerical statements of facts in any department of enquiry, placed in relation to each other”. - Dr. A. L. Bowley “statistics is the science of collection, presentation, analysis, and interpretation of numerical data”. -Croxton and Cowden
- 5. OBJECTIVES OF STATISTICS: 1. To draw conclusions about a population followed by an analysis of information contained in sample data. This includes assessing the degree of uncertainty in these inferences. 2. To plan the process and the observations can be used to draw valid conclusions. 3. To determine the type and quantity of data that must be collected. 4. To analyse and draw conclusions from the data. 5. To assess the conclusions strengths and evaluate their uncertainty.
- 6. TYPES OF STATISTICS: Descriptive statistics: descriptive statistics describe, show, and summarize the basic features of a dataset found in a given study, presented in a summery that describes the data sample and its measurements. It helps analysts to understand the data better. two main types of descriptive statistics: 1. Measures of central tendency Mean Median Mode 2. Measures of dispersion or variance variance Standard deviation Range
- 7. INFERENTIAL STATISTICS: inferential statistics is a branch of statistics that makes the use of various analytical tools to draw inferences about the population data from sample data. Two types of inferential statistics 1. Hypothesis testing 2. Regression analysis
- 8. Advantages of statistics: 1. Making sense of data 2. Identifying patterns and trends 3. Making predictions 4. Making decisions 5. Communicating information
- 9. Disadvantages of statistics: 1. Complexity 2. Bias 3. Limited scope 4. False sense of certainty 5. overreliance
- 10. Important terminologies of statistics:
- 11. THANK YOU