Module 1 Introduction to Statistics.pptx
- 1. Module 1: Introduction to Statistics By: Kishlay Kumar Assistant Professor Faculty of Business Management Sarala Birla University, Ranchi
- 2. What is statistics? • Statistics is the study and manipulation of data, including ways to gather, review, analyze, and draw conclusions from data. • The word statistics refers either to quantitative information or to a method of dealing with quantitative information. • Statistics can be used to make better-informed business and investing decisions.
- 3. Function of Statistics Presents facts in. simple form Reduces the Complexity of data Facilitates comparison Helps in formulating Hypothesis Helps in Planning
- 4. Scope of statistics Statistics in Business and Management Statistics in Economics Statistics in State Administration( Defence,Population, Taxes Etc) Statistics in Research Statistics and Physical Science
- 5. Collection of Data Data collection is defined as the procedure of collecting, measuring and analyzing accurate insights for research using standard validated techniques. Data collection is generally done after the experiment or observation. Data collection is helpful in planning and estimating. Data collection is either qualitative or quantitative. Data collection methods are used in businesses and sales organizations to analyze the outcome of a problem, arrive at a solution, and understand a company’s performance. Data can be obtained from two important sources: (a) Primary Source (b) Secondary Data
- 7. Primary Data Primary Data are measurement observed and recorded as part of an original study. Primary data is often reliable, authentic, and objective in as much as it was collected with the purpose of addressing a particular research problem. It is noteworthy that primary data is not commonly collected because of the high cost of implementation. There are two basic methods of obtaining primary data: (a) Questioning ( b) Observation.
- 8. Primary Data Collection Methods Personal or Face to Face Interview Telephonic Interview Questionnaire Observation
- 9. Questionnaire A questionnaire is a research instrument that consists of a set of questions or other types of prompts that aims to collect information from a respondent. Questionnaires are commonly used to gather first-hand information from a large audience, in the form of a survey. Questionnaires are highly practical and can be carried out by any number of people, and the results can be quickly quantified as well. A research questionnaire is typically a mix of close ended questions and open ended questions.
- 10. Open Ended Questionnaire Questions that allow the target audience to voice their feelings and notions freely. These questions are not based on pre-determined responses, giving respondents an opportunity to express what they feel is right, and often provide real, perceptional, and at times. Open-ended questions placed at the end of a questionnaire tend to draw accurate feedback and suggestions from respondents as well.
- 11. Closed Ended Questionnaire Close ended questions are defined as question types that ask respondents to choose from a distinct set of pre-defined responses, such as “yes/no” or among set multiple choice questions. Closed-ended questions come in a multitude of forms but are defined by their need to have explicit options for a respondent to select from. There are various type of closed ended questionnaire:- a) Dichotomous Question
- 12. b) Multiple choice question Type of Multiple choice questions: I. Likert Scale Multiple Choice Questions: These closed ended questions, typically are 5 pointer or above scale questions where the respondent is required to complete the questionnaire that needs them to indicate the extent to which they agree or disagree.
- 13. II. Rating Scale Multiple Choice Questions: These close ended questions require the respondents to assign a fixed value in response, usually numeric. The number of scale points depends on what sort of questions a researcher is asking. III. Checklist type Multiple Choice Questions:This type of closed ended question expects the respondents to make choices from the many options that have been stated, the respondent can choose one or more options depending on the question being asked.
- 14. IV. Rank Order Multiple Choice Question: These closed ended questions come with multiple options from which the respondent can choose based on their preference. From most preferred to least preferred.
- 15. Secondary Data Secondary data is the data that has been collected in the past by someone else but made available for others to use. They are usually once primary data but become secondary when used by a third party. Secondary data are usually easily accessible to researchers and individuals because they are mostly shared publicly. This, however, means that the data are usually general and not tailored specifically to meet the researcher's needs as primary data does.
- 16. Questions Q.1. Identify the method you will use for the data collection of the given scenario: To know the preferred brand of clothing of a particular age group. Q.2. Identify the method you will use for the data collection of the given scenario: To know the average rainfall recorded in a year. Q.3. Identify the type of method for data collection (Qualitative or Quantitative) used for the given scenario: How well would you recommend the institution to another person for taking up the course? Q.4. Identify the type of method for data collection (Qualitative or Quantitative) used for the given scenario: To know the number of people who attended the training.
- 17. Presentation of Data After data have been collected, the very next step is to present the data in suitable form. When data are presented in easy to read form, it can help the reader to acquire knowledge in much shorter period of time.
- 18. Classification of data Classification is the process of arranging data into sequences and groups according to their common characteristics, or separating them into different but related parts. It is the process of arranging data into homogeneous (similar) groups according to their common characteristics. For instances the number of students registered in SBU during the academic year 2021 – 24 may be classified on the basis of any of the following criterion : (i) Gender (ii) Age (iii) The state to which they belong ) Religion (v) Different faculties, like Science, Humanities, Law, Commerce, etc. (vi) Heights or weights and so on
- 19. Type of Classification Data can be classified on the following four bases : (i) Geographical i.e., Area-wise or Regional. (ii) Chronological i.e., on the basis of time. (iii) Qualitative i.e., according to some character or attribute. (iv) Quantitative i.e., in terms of numerical values or magnitude
- 20. Geographical Classification: In this classification the basis of classification is the geographical or locational differences between the various items in the data like States, Cities, etc. For Eg: City Population( in lakhs) Delhi 325 Mumbai 648 Chennai 422 Kolkata 322 Ranchi 75 Patna 148
- 21. Chronological Classification: Chronological classification is one in which the data are classified on the basis of differences in time. Year Sales (in lakhs) 2011-12 18819 2012-13 20159 2013- 14 23601 2014-15 28987 2015-16 31098 2016-17 33987 2017-18 39852 2018-19 43985 2019-20 49641
- 22. Qualitative classification: When the data are classified according to some qualitative phenomena which are not capable of quantitative measurement like honesty, beauty, employment, intelligence, occupation, sex, literacy, etc., the classification is termed as qualitative or descriptive or w.r.t. attributes. In qualitative classification the data are classified according to the presence or absence of the attributes in the given units. If the data are classified into only two classes w.r.t. an attribute like its presence or absence among the various units, the classification is termed as simple classification.
- 23. If instead of forming only two classes we further divide the data on the basis of some attribute or attributes so as to form several classes , the classification is known as manifold classification.
- 24. Quantitative Classification: If the data are classified on the basis of phenomenon which is capable of quantitative measurement like age, height, weight, prices, production, income, expenditure, sales, profits, etc., it is termed as quantitative classification. Monthly Wages (Rs) No. of workers 4000- 4500 50 4500-5000 200 5000-5500 260 5500-6000 360 6000-6500 90 6500-7000 40 Total 1000
- 25. Frequency Distribution A frequency distribution is the representation of data, either in a graphical or tabular format, to displays the number of observation within a given integral. In Statistics, a frequency distribution is a table that displays the number of outcomes of a sample. Each entry occurring in the table contains the count or frequency of occurrence of the values within a group.
- 26. Question A survey was taken on Maple Avenue. In each of 20 homes, people were asked how many cars were registered to their households. The results were recorded as follows: 3, 1, 4, 0, 2, 1, 5, 2, 1, 5, 4, 2, 3, 2, 0, 2, 1, 0, 3, 2. Number of Cars Frequency 0 3 1 4 2 6 3 3 4 2 5 2
- 27. Tabulation of Data Tabulation is a systematic and logical representation of numeric data in rows and columns to facilitate comparison and statistical analysis. It facilitates comparison by bringing related information close to each other and helps in statistical analysis and interpretation. Objectives Of Tabulation: To simplify complex data To bring out essential features of data To facilitate comparison To facilitate statistical analysis
- 28. Parts of a Table The various parts of table may vary from case to case depending upon the given data. But a good table must contain at least the following parts: a) Table Number b) Title of the table c) Caption d) Stub e) Body of the table f) Headnote g) Footnote
- 30. Simple and Manifold Tabulation Simple Tabulation: only one charateristics Manifold Tabulation: Two or more characteristics.
- 31. Graphs of Frequency Distribution Histogram Frequency Polygon Smoothed frequency curve Ogives