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INSTRACTOr: BILAL KHAN MBA(MARKETING) Msc (Economics). MIHE:. Introduction to business Statistics. Chapter No 01. What is statistics?. Numerical data relating to an aggregate of individuals, the science of collecting, analyzing and interpreting data is called statistics. Conti….
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Introduction to business Statistics. Chapter No 01
What is statistics? • Numerical data relating to an aggregate of individuals, the science of collecting, analyzing and interpreting data is called statistics.
Importance of statistics in Business. • Statistics play an important role in business, because provides a quantitative basis for arriving at decisions in all matters connected with operating of business. • For example producers must know the demand of his consumers. • Statistics would help to plan production according to the demands of consumers
Conti………… • The banks make use of statistics while framing their policies. The banks have to conduct constant enquiries regularly deposits under different categories, the nature of demand for daily with-drawls etc.
Difference between Parameter and statistic. • Parameter. • A number that describes some property of a population is called parameter • For example a numerical value such as mean and mode etc…..
Conti……… • Statistic. • A number that describes some property of a sample is called statistic. • For example the average length calculated for a random(hit and miss) sample of a college students.
Difference between population and sample. • Population. • The aggregate or totality of all the individual items about which information is required is called population • For example if 1000 students in the college that we classified according to blood type.
Conti……. • Sampling. • The study of observing the single part or only a part of the population , such a part is called sampling.
Difference between Descriptive and inferential statistics. • Descriptive statistics. • Those statistics method which is concerned with collecting and describing a set of data so as to yield meaningful information. • For example teacher computes an average grade for his statistics class. The average grade describes the performance of that particular class.
Coati….. • Inferential statistics. • Those statistics methods which is concerned with the analyzing of a subset of a data leading to inference about the entire set of a data. • For example the academic records of the metric classes during the past five years at a nearby government school show that 45% of the entering freshmen eventually matriculated.
What is variable. • A quantity which may take any one of a specified set of values. • For example the height of a students, rainfall at a place, price of a commodity etc.
Discrete Variable. • A discrete variable can assume only a finite number. • For example the number of children in a family, the number of goals scored by a player etc.
Continuous variable • A continuous variable may take an infinite number of values between any two points such as the height of a student, the temperature at a place etc.
Quantitative variable. • If the values are expressed numerically the variable is said to be quantitative. • Foe example age, weight, income, number of children etc.
Qualitative variable. • If the values are not expressed in the numerical form is called qualitative variable. • For example smoking, poverty intelligence etc.
Chapter no 2 • Collection • and • Presentation • Of data.
What do you mean by classification. • Classification. • It is the process of arranging data into sequences and groups according to their common characteristics. • For example we may arrange the marks into group of 60 marks each like 01 to 59, 60 t0 119 etc.
Types of classification: • 1: Descriptive • 2:Numerical.
Descriptive classification: • When the data are classified on the basis of quality which are incapable of quantitative measurement the classification is said to be descriptive. • For example classification according to the sex and marital status divide the population into six classes. • Male married • Male unmarried • Male widowed • Female married • Female unmarried • Female widowed
Numerical Classification • This type of classification is applicable to quantitative data only. • For example data related to the height, weight, income and production etc.
What do you mean by tabulation of statistical data • Tabulation simply means presenting of data through tables. • It is the next of classification in the process of statistical investigation. • To be more precise tabulation is an orderly arrangement of data into columns and rows.
Simple tabulation • A simple tabulation contains data regarding one characteristics only. • Information relating to the other characteristics being ignored.
Complex tabulation • Shows the division of the data into two or more categories:
Distribution… • Arrangement of data according to the values of a variable characteristics is called distribution
What is frequency distribution? • A large mass of data possessing different characteristics is grouped into different classes. • The observation are determined in each class. • The arrangement of these classes into tabular form makes frequency distribution.
Class frequency and grouped data • The number of observation falling in a class makes a class frequency. • Data organized and summarized in the form of frequency distribution are called grouped data.
Main points of preparing a frequency distribution • Number classes and their lengths • Class-Limit • Class boundaries • Class-Marks or Mid point • Class frequency
Number of classes and their lengths • A frequency distribution should not have too few or too many large. • Depending upon a particular data. • The number of classes should not exceed 25 and should not be less than 6.
Class Limit • The limit of the class should be so fixed that the mid point of each class interval fall on an integer and not a fraction
Class boundaries • If one have grouped frequency distribution with class limit having a gap between the upper class limit of one class and the lower class limit of the next class
Class-Marks or Mid point • Formula : lower class + upper class • 2
Class frequency • The frequency of a class interval is the total number of items falling in that class interval • Also called class tally sheet • Usually after every four lines in a class the fifth item is marked by horizontal or slanted lines across the strokes
Q : make a group frequency distribution from the following data . • 106 107 76 82 109 107 115 93 95 123 125 • 111 92 86 70 126 68 130 129 139 119 115 • 128 100 186 84 99 113 204 111 141 136 123 90 115 • 98 110 78 185 162 178 140 112 173 146 158 194 • 148 90 107 181 131 75 184 104 110 80 118 82. • By scanning the data we find that the largest weight is 204 and the lowest is 68 so the range is 204-68=136 • Decide on the number of classes into which the data are to be grouped we used H.A Sturges rule. • K= 1+3.3logN. • Where k denotes the number of classes and N is the total number of observation.
Conti…. • Frequency distribution.
Q: arrange the data given below in an array and construct a frequency distribution using a class interval of 5 indicate the class boundaries and class limit clearly • 79.4, 71.6, 95.5, 73, 74.2, 81.8, 90.6, 55.9, 75.2, 81.9, 68.9, 74.2, 80.7, 65.7, 67.6, 82.9, 88.1, 77.8, 69.4, 83.2, 82.7, 73.8, 64.2, 63.9, 58.3, 48.6, 83.5, 70.8, 72.1, 71.9, 59.4, 77.6 • Ans: the value of variate range from 48.6 to 95.5. we take class interval of length 5. • No. of classes = range • class interval • 95.5 – 48.6 = 9.38 = 10 • 5
What is simple bar chart: • The simple bar chart is particularly appropriate for a linear or one dimension comparison. The scale for construction of simple bar chart should be such as facilitates the representation of largest bar quite conveniently.
Chart…. 80 60 40 20 0 1998 1999 2000 2001 2002
Multiple bar chart • In this type of chart we represent two or more than two sets of a data in one chart than more than one chart is used. • This can be explained with the help of example, the following table give the imports and exports of Pakistan for year 1992 to1997.
