Chapter 3 DATA PROCESS & ANALYSIS OF STATISTICS Dr. BALAMURUGAN MUTHURAMAN

DATA PREPARATION AND ANALYSIS Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names in different business, science, and social science domains

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STATISTICAL MEASURES Mean – Average of the series Median – Divides the data-set into two category. Mode – Most occurring digit in series Range – Difference between the highest and lowest value. Median Deviation – The average of difference of the values of items from some average of the series. Standard Deviation – The square-root of the average of squares of deviations. Coefficient of Skewness – It gives the idea of the shape of data distribution by Histogram

Practical Exercise A Manufacturer of shoes is interested in finding out the size most in demand in Oman so that he may manufacture a larger quantity of that size. For that purpose he collected information about 20 people about their size as below: 6,7,8,9,10,11,6,7,8,9,10,6,7,8,10,7,8,7,6,7, Calculate  Mean  Median  Mode  Range  Mean Deviation  Standard Deviation  Coefficient of Skewness

Practical Exercise A Class of 20 students in a school has the following weight in Kg. The Dietician wants to know the following information for his research work. For that purpose he collected information about 20 students about their weight as below: 26,27,28,29,30,31,26,27,28,29,30,26,27,28,30,27,28,27, 26,27 Calculate  Mean, Median, Mode and Range  Mean Deviation, Standard Deviation and Coefficient of Skewness

MEASUREMENT AND SCALING In marketing research, numbers are usually assigned for one of two reasons. 1. Numbers permit statistical analysis of resulting data. 2. Numbers help the communication of rules and result. SCALING: The generation of a continuum upon which measured objects are located, also involves creating a continuum upon which measured objects are located. Is process of placing the respondent on continuum with respect to their attitude toward department store. 1 = extremely unfavorable ; 100 = extremely favorable

PRIMARY SCALES MEASUREMENT There are four primary scales of measurements:  Nominal  Ordinal  Interval  RatioNOMINAL A scale whose numbers serve only as labels or tags for identifying and classifying objects. When used for identification, there is strict one-to-one correspondence between the numbers and the objects. In marketing research, nominal scale are used. The numbers on a nominal scale do not reflect the amount of characteristics possessed by the objects

The only permissible operation on the numbers in a nominal scale is counting only a limited number of statistics, all of which are based on frequency counts, are permissible these include percentages, mode etc.ORDINAL Ranking scale in which numbers are assigned to objects to indicate the relative extent to which some characteristics is possessed. Thus it is possible to determine whether an object has more or less of characteristics than some other object. An ordinal scale indicates relative position.  Example of ordinal scale include quality ranking, ranking if teams in a tournament, socioeconomics classes, and occupational status. In marketing research ordinal scale used to measure relative attitude, opinions, perceptions and preference

INTERVAL  A scale in which the numbers are used to rate objects such that numerically equal distances on the scale represent equal distances in the characteristic being measured.  There is a constant or equal interval between scale values.RATIO  The highest scale, it allows the researcher to identify or classify objects, and compare intervals or differences. It is also meaningful to compute ratios of scale values

COMPARISON OF SCALING TECHNIQUES COMPARISON OF SCALING TECHNIQUES The scaling techniques commonly employee in marketing research can be classified into: Comparative Scales  Paired comparison scaling  Rank order scaling  Constant sum scaling Non-comparative Scales  Continuous rating scales  Itemized rating scales  Likert scales

COMPARATIVE SCALE COMPARATIVE SCALE Is one of two types of scaling techniques in which there is direct comparison of stimulus objects with one others. Comparison scales include Paired comparisons, Rank Order, Constant sum scales, Q-sort. Advantages  Comparative scales are easily understood and can be applied easily.  They involve smaller quantity theoretical assumptions  Reduce the halo effects or carryover effects from one judgment to another. Disadvantage The ordinal nature of the data and the inability to generalize beyond the comparative scales

NON-COMPARATIVE SCALES One of two types of scaling techniques in which each stimulus object is scaled independently of other objects in the stimulus set. Also referred to as monadic or metric scales. Each object is scaled independently of the others in the stimulus set. The itemized rating scales can be further classified as likert, semantic differential, or stapel scales. It is the most widely used scaling technique in marketing research

Practical Exercise A Manufacturer of shoes is interested in finding out the size most in demand in Oman so that he may manufacture a larger quantity of that size. For that purpose he collected information about 30 people about their size as below: 6,7,8,9,10,11,12,6,7,8,9,10,11,6,7,8,10,7,8,7,6,7,6,7,8,8,9.10,6,7. Calculate  Mean  Mode  Range  Mean Deviation