{"id":16483,"date":"2024-03-11T07:15:18","date_gmt":"2024-03-11T01:45:18","guid":{"rendered":"https:\/\/wordpress-505192-1602719.cloudwaysapps.com\/?p=16483"},"modified":"2024-03-12T15:39:51","modified_gmt":"2024-03-12T10:09:51","slug":"samacheer-kalvi-12th-business-maths-solutions-chapter-8-ex-8-1","status":"publish","type":"post","link":"https:\/\/samacheerkalviguru.com\/samacheer-kalvi-12th-business-maths-solutions-chapter-8-ex-8-1\/","title":{"rendered":"Samacheer Kalvi 12th Business Maths Solutions Chapter 8 Sampling Techniques and Statistical Inference Ex 8.1"},"content":{"rendered":"

Students can download 12th Business Maths Chapter 8 Sampling Techniques and Statistical Inference Ex 8.1 Questions and Answers, Samacheer Kalvi 12th Business Maths Book Solutions<\/a> Guide Pdf helps you to revise the complete Tamilnadu State Board New Syllabus and score more marks in your examinations.<\/p>\n

Tamilnadu Samacheer Kalvi 12th Business Maths Solutions Chapter 8 Sampling Techniques and Statistical Inference Ex 8.1<\/h2>\n

Question 1.
\nWhat is the population?
\nSolution:
\nA population is a set of similar items or events which is of interest for some question or experiment. A population can be specific or vague. Examples of population defined vaguely include the number of newborn babies in Tamil Nadu, a total number of tech startups in India, the average height of all exam candidates, mean weight of taxpayers in Chennai etc. Examples of population defined specifically include a number of fans produced in a particular factory, the number of students in a class, the number of boys and girls in a tuition centre etc.<\/p>\n

Question 2.
\nWhat is the sample?
\nSolution:
\nA sample is a set of data collected from a statistical population by a defined procedure. The elements of a sample are called sample size or sample points. Samples are collected and statistics are calculated from the samples, so that one can make inferences from the sample to the population.<\/p>\n

\"Samacheer<\/p>\n

Question 3.
\nWhat is statistic?
\nSolution:
\nA statistic is used to estimate the value of a population parameter. For instance, we selected a random sample of 100 students from a school with 1000 students. The average height of the sampled students would be an example of a statistic. Examples, sample variance, sample quartiles, sample percentiles, sample moments etc.<\/p>\n

Question 4.
\nDefine parameter.
\nSolution:
\nA parameter is any numerical quantity that characterizes a given population or some aspect of it. This means the parameter tells us something about the whole population. For example, the population mean \u00b5, variance \u03c32, population proportion P, population correlation \u03c1.<\/p>\n

\"Samacheer<\/p>\n

Question 5.
\nWhat is the sampling distribution of a statistic?
\nSolution:
\nSampling distribution of a statistic is the probability distribution of a given random sample based statistic. It may be considered as the distribution of the statistic for all possible samples from the same population of a given sample size.
\nExample, the sampling distribution of the mean for n = 2 is given below:
\n\"Samacheer<\/p>\n

Question 6.
\nWhat is the standard error?
\nSolution:
\nThe standard error (S.E) of a statistic is the standard deviation of its sampling distribution. If the parameter or the statistic is the mean, it is called the standard error of the mean (SEM). The standard error provides a rough estimate of the interval in which the population parameters is likely to fall.
\n\"Samacheer<\/p>\n

\"Samacheer<\/p>\n

Question 7.
\nExplain in detail about simple random sampling with a suitable example.
\nSolution:
\n(i) Simple random sampling:
\nIn this technique, the samples are selected in such a way that each and every unit in the population has an equal and independent chance of being selected as a sample. Simple random sampling may be done, with or without replacement of the samples selected. In a simple random sampling with replacement, there is a possibility of selecting the same sample any number of times. So, simple random sampling without replacement is followed.
\nThus in simple random sampling from a population of N units, the probability of drawing any unit at the first draw is \\(\\frac{1}{N}\\), the probability of drawing any unit in the second draw from among the available (N – 1) units is \\(\\frac{1}{(N-1)}\\), and so on. Several methods have been adopted for random selection of the samples from the population. Of those, the following two methods are generally used and which are described below.<\/p>\n

1. Lottery method
\nThis is the most popular and simplest method when the population is finite. In this method, all the items of the population are numbered on separate slips of paper of the same size, shape and colour. They are folded and placed in a container and shuffled thoroughly. Then the required numbers of slips are selected for the desired sample size. The selection of items thus depends on chance.<\/p>\n

For example, if we want to select 10 students, out of 100 students, then we must write the names\/roll number of all the 100 students on slips of the same size and mix them, then we make a blindfold selection of 10 students. This method is called unrestricted random sampling because units are selected from the population without any restriction. This method is mostly used in lottery draws. If the population or universe is infinite, this method is inapplicable.<\/p>\n

2. Table of Random number
\nWhen the population size is large, it is difficult to number all the items on separate slips of paper of same size, shape and colour. The alternative method is that of using the table of random numbers. The most practical, easy and inexpensive method of selecting a random sample can be done through \u201cRandom Number Table\u201d. The random number table has been so constructed that each of the digits 0, 1, 2,…, 9 will appear approximately with the same frequency and independently of each other.<\/p>\n

The various random number tables available are<\/p>\n