BBM203/05 Business Statistics TMA1 Weightage: 25% Submission deadline: 6th March 2015 1 a) Explain TWO (2) main differences between qualitative data and quantitative. (4 marks) b) Using the example of a group of BBM203/05 students in your class‚ differentiate qualitative and quantitative data. (6 marks) 2) A new restaurant did a survey among its customers recently. The following questions were asked in the questionnaire. Identify which type of data are they? Choose from Qualitative-Nominal‚ Qualitative-Ordinal
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side effects resulting in low self-esteem‚ eating disorders‚ or depression. Media projects images of women that have been surgically or technologically edited‚ these projections are causing negative effects. These unrealistic women have a greater effect on young women today‚ society has enveloped this idea that we have to meet this certain image. We have become so overwhelmed with the stereotypical image causing great disapproval for women who are slightly overweight. Everyone wants to look their
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number of items in several classes is a a. frequency distribution b. relative frequency distribution c. frequency d. cumulative frequency distribution Answer: b 4. Qualitative data can be graphically represented by using a(n) a. histogram b. frequency polygon c. ogive d. bar graph Answer: d 5. The relative frequency of a class is computed by a. dividing the midpoint of the class by the sample size b. dividing the frequency of the class by the midpoint c. dividing
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lakhs. List all customers whose name starts with ’ba’. List names of all customers in descending order who has taken a loan in Nasik city. Display customer details having maximum loan amount. Calculate total of all loan amount. Q.3) Draw a histogram to represent the following frequency distribution using MS Excel. Size of farm In hectares 1-20 21-40 41-60 61-80 81-100 101-120 No. of farms 12 38 16 5 3 1 [10 Marks] Q.4) Journal [10 Marks]
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INTELLIGENT TRANSPORTATION SYSTEMS‚ VOL. 9‚ NO. 3‚ SEPTEMBER 2008 377 License Plate Recognition From Still Images and Video Sequences: A Survey Christos-Nikolaos E. Anagnostopoulos‚ Member‚ IEEE‚ Ioannis E. Anagnostopoulos‚ Member‚ IEEE‚ Ioannis D. Psoroulas‚ Vassili Loumos‚ Member‚ IEEE‚ and Eleftherios Kayafas‚ Member‚ IEEE Abstract—License plate recognition (LPR) algorithms in images or videos are generally composed of the following three processing steps: 1) extraction of a license plate
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Data Analysis • Describing data and datasets Introduction to Data Analysis and Decision Making • Making inferences from data and datasets • Searching for relationships in data and datasets Decision Making Uncertainty • Optimization • Measuring uncertainty • Decision analysis with uncertainty • Modeling and simulation • Sensitivity Analysis 1 What is Management Science? • Logical‚ systematic approach to decision making using quantitative methods. • Science
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displayed. Data displayed will relate to things like amounts‚ characteristics‚ times and frequency etc. A bar graph displays information in a way that helps us to make generalizations and conclusions quickly and easily. histograph Line-chart based on a histogram‚ it is drawn by joining the mid-points of the blocks at their apexes with a straight line. The extreme points of the line are joined to the horizontal (’X’) axis (where the mid-point of the respective next class would have been) to result into a polygon
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Frequency Distribution (A) Introduction 1. Ungrouped data versus grouped data Ungrouped data (Raw data): It is a list of individual observed values of the random variable Grouped data (a frequency distribution): It is a table that displays the data in grouping along with the number of occurrences that fall into each group. 2. The components of a frequency distribution a. Class limits: They identify the inclusive values in a class of a frequency distribution The
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1. A recent issue of Fortune Magazine reported that the following companies had the lowest sales per employee among the Fortune 500 companies. [20 Marks] | |Company |Sales per Employee ($1000s) |Sales Rank | | |Seagate Technology |$42.20 |285 | | |SSMC | 42.19
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“EXTRACTION AND QUANTIFICATION OF BRAIN TUMOR FROM MRI IMAGE” CHAPTER 1 INTRODUCTION 1.1 GENERAL: The principle task of our project is to recognize a tumor and its quantifications from a particular MRI scan of a brain image using digital image processing techniques and compute the area of the tumor by fully automated process. In medical imaging‚ segmentation of images plays a vital role in stages which occur before implementing object recognition
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