3.1 Using data from Kellogg’s business scenario‚ prepare a range of graphs using spreadsheets — line‚ pie‚ bar charts and histograms‚ and draw valid conclusions based on the information derived (P7) For collecting data from the people of India about their breakfast habit and attitude the student worked by dividing themselves into 4 groups with the same questionnaires. They provide it to 125 peoples a total and they have answered properly. The students have made some data basis chart depending on
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QUANTITATIVE METHODS - STATISTICS ------------------------------------------------- (SUBJECT CODE: STA1114) ------------------------------------------------- Instructions to Students: 1. Assignment questions consist of: * Question One - 25% * Question Two - 25% 2. Assignment question must be combined into ONE (1) booklet‚ attached with “Assignment Submission Form” as the front cover‚ enclosed with the “Marking Criteria.” typed with double spacing
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Q1: 3109.3 Variance: 868429.8 Median: 4090 Skew: -0.15043 Q3: 4747.5 N: 50 Max: 5678 The histogram above shows the Credit Balance variable of the 50 customers surveyed. The histogram is almost symmetrical with one outlier which is the credit balance of $2‚000. While it being symmetrical you can almost fold the y-axis in half to have it look the same. While observing the histogram‚ its skewed to the left because of the outlier‚ and the skew is -.015043. Using the Anderson-Darling Normality
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30/04/2012 Word Count (Without contents‚ References and Title page): 2‚497 Contents 1.1 - Introduction – Page 3 2.1 – Data set‚ Annual GDP % Change Comparisons – Page 3 2.2- The mean – Page 3 2.3- The Median – Page 4 2.4- Histograms – Page 4 2.5- The Range – Page 5 2.6- Simple Linear Regression – Page 6 3.1- Time series analysis – Line Graph (Cyclical) – Page 8 4.1- Conclusion – Page 8 5.1- References – Page 9 1.1 Introduction In this report I will
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background. Fourthly there is the frequency distribution. In the frequency distribution is a summary of the ranges of values. Frequency distribution can be shown by the team in graphic or tables that will be presented. Finally the use of the histogram will be depicted in the team analysis of the data that was collected. |Descriptive statistics | | | | | |
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counts of this categorical variable. Comment on its shape. 3. Problem 2.6 (p. 55) The file P02_06.xlsx lists the average time (in minutes) it takes citizens of 379 metropolitan areas to travel to work and back home each day. a. Create a histogram of the daily commute times. b. Find the most representative average daily commute time across this distribution. c. Find a useful measure of the variability of these average commute times around the mean. d. The empirical rule for standard deviation
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Representation and Summary of data [10/09/12] Histograms * To be able to draw and interpret histograms. * Continuous Data:- * Measured [Rounded off to a particular degree of accuracy] * Time * Length * Speed – Velocity * Mass – Acceleration * Volume * Density * Area * Most suitable for a histogram. The area of a histogram is proportional to its frequency. Area ∞ Frequency
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project. Part one was sampling. We were to purchase 3 bags of M&M and record the color counts of each bag in an Excel spread sheet. For part two we calculated the sample proportions for each color‚ the mean number of candies per1.69oz bag‚ created a histogram for the number of candies per bag‚ use Excel to compute the descriptive statistics for the total number of candies per bag and summarize the information. In part three we located the 95% confidence interval for the proportion of blue‚ orange‚ green
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operators such as Sobel‚ Prewitt and Roberts. Secondly‚ a comparative study is made to show that the Sobel operator gives best results.Finally‚ Edge extraction using edge histogram is taken into account. The edge extraction method proposed in this paper is feasible. Index terms: digital image‚ edge detection‚ operators‚ edge histogram. Introduction: The edge is a set of those pixels whose grey have stepchange and rooftop change‚ and it exists between object andbackground‚ object and object‚ region
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Confidence Interval: $1.06 to $44.62 The histogram is present in appendix A; the descriptive statistics are present in appendix B. Age Distribution: State if not normally distributed Central Tendency: Median = 35 years Dispersion: Interquartile Range = 12 Years / 2 = ± 6 Years Number: 100 Min/Max: Min is 25 Years; Max is 45 Years Confidence Interval: The data is not normally distributed‚ therefore there is no confidence interval. The histogram is present in appendix A; the descriptive
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