Chapter 8 — Use of Statistical Tools

Chapter 8 is titled 'Use of Statistical Tools'. It teaches students how to design a statistical project and apply tools such as questionnaires, tabulation, diagrams, measures of central tendency, measures of dispersion, and correlation to analyse economic problems. Statistical tools are described as important for analysis of data on production, consumption, distribution, banking, insurance, trade, and transport.

The chapter outlines six steps: (1) identifying the problem or area of study, (2) choosing the target group, (3) collecting data using primary or secondary methods, (4) organising and presenting data with tables and diagrams, (5) analysing and interpreting data using statistical measures, and (6) drawing meaningful conclusions. A bibliography of secondary sources must also be included.

Primary data is collected firsthand through questionnaires or interview schedules via personal visits, postal surveys, phone, or email. Secondary data is used when there is a paucity of time, money, and manpower and the information is easily available. The objective of the survey determines whether primary, secondary, or both methods are used.

The target group determines what questions to frame in the questionnaire and whom to survey. For example, a car project targets middle and higher income groups, while a soap project targets all rural and urban consumers, and a safe drinking water project can target both urban and rural populations. Choosing the right group ensures relevant data is collected.

After collection, data is processed by organising it through tabulation and presenting it using suitable diagrams such as bar diagrams, pie diagrams, and histograms. The chapter references tabulation and diagrammatic techniques covered in earlier chapters (Chapters 3 and 4) of the textbook.

The chapter specifies measures of central tendency (such as mean), measures of dispersion (such as standard deviation), and correlation. These enable the researcher to calculate averages, variability, and the relationship between variables. These concepts are covered in Chapters 5 and 6 of the textbook.

The sample project was a toothpaste market study for an entrepreneur (X) who wanted to set up a toothpaste factory. Primary data was collected from 100 households using a questionnaire covering monthly expenditure on toothpaste, current brand usage, ingredient preferences, satisfaction levels, and major media influences on buying decisions.

67% of the 100 surveyed households were urban and 33% rural. Mean monthly family income was Rs. 18,000 with a standard deviation of Rs. 9,000. Mean monthly expenditure on toothpaste per household was Rs. 104 with a standard deviation of Rs. 35.60. Pepsodent, Colgate, and Close-up were the most preferred brands, and television was the most influential advertising medium (47 families).

A questionnaire is the primary tool for firsthand data collection. It must be designed to capture all information needed — such as income, family size, brand preference, and media habits. If a previously tested questionnaire is available for a similar study, it can be modified suitably. Postal questionnaires must include a covering letter explaining the purpose of the inquiry.

The conclusion summarises the meaningful findings after analysis and interpretation of the data. The chapter states that, where possible, students should also try to predict future prospects and make suggestions relating to growth and government policies based on the information collected.

The chapter lists 12 suggested topics, including: preparing a transportation system report for a Transport Minister, a bank loan project proposal for a cottage industry, a report on the effect of advertisements on product sales, assessing school dropout reasons as a District Education Officer, investigating MRP overcharging by traders, and studying saving habits of people as a Bank Officer.

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