HISTOGRAM INTRODUCTION Histogram * Histograms are graphs of a distribution of data designed to show centring‚ dispersion (spread)‚ and shape (relative frequency) of the data. * Histograms can provide a visual display of large amounts of data that are difficult to understand in a tabular‚ or spreadsheet form. * A histogram shows much the same information as a stem plot‚ though for a given dataset one or the other of these methods of displaying the data may be preferable.
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QRB Concepts – Plotting Bivariate data Concept: Construct histograms and bivariate plots using Excel. Reading Reference: Topic 2 of Sevilla & Somers and Ch. 4 of Lind‚ Marchal‚ & Wathen Example of Application Bivariate Plots: Economics: We often need to plot a demand curve to illustrate levels of quantity demanded based on the price of a product. Bivariate plots can be used to project future sales based on pricing or to determine if a price is too high or low. People typically buy more
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Joey Stevens QMM 240 TR 10:00-11:15 Computer Assignment #1 1. a. Excel Histograms Bins MPG | Frequency | 11 | 1 | 16 | 3 | 21 | 16 | 26 | 34 | 31 | 13 | 36 | 9 | 41 | 2 | 46 | 2 | Bins Weight | Frequency | 1300 | 1 | 1780 | 7 | 2260 | 18 | 2740 | 12 | 3220 | 22 | 3700 | 11 | 4180 | 7 | 4660 | 2 | b. I chose the number of classes based on the Sturges’ Rule table. I knew I had 80 observations so that put me between either 7 or 8
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3.5.4 Problem in Histogram Equalization 1. This histogram equalization method does not take the mean brightness of an image into account. 35 2. The HE method may result in over enhancement and saturation art effects due to the stretching of the gray levels over the full gray level range. 3. HE can be found on the fact that the brightness of an image can be changed after the HE. 4. Nevertheless‚ HE is not commonly used in consumer electronics such as TV because it may significantly change the brightness
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to create a Histogram in Excel First‚ the Data Analysis "toolpak" must be installed. To do this‚ pull down the Tools menu‚ and choose Add-Ins. You need to have a column of numbers in the spreadsheet that you wish to create the histogram from‚ AND you need to have a column of intervals or "Bin" to be the upper boundary category labels on the X-axis of the histogram. See example of spreadsheet below: Pull Down the Tools Menu and Choose Data Analysis‚ and then choose Histogram and click OK
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band in order to preserve edges and to reduce noise . A Contrast Limited Adaptive Histogram Equalization (CLAHE) technique is used. To enhance the contrast and the separability between exudates and the background ‚ a Contrast Limited Adaptive Histogram Equalization (CLAHE) technique is used which consists of subdividing the image into non-overlapping rectangular regions and then applying their local equalization histogram. B. Blood vessel Detection and Elimination The exact detection of artery
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figure 5(b). 5.2 Histogram analysis For every stage images (front and back) of twenty five leaves are randomly selected from healthy
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A. Constructing and interpreting graphical displays of distribution of univriate data (dotplot‚ stemplot‚ histogram‚ cumulative frequency plot) 1. Center = location Spread = variablility 2. Clusters are isolated groups of data points. Gaps refer to missing areas in a data set. 3. Outliers are extreme values‚ data points that lie significantly outside other values in a data set. Unusual features are gaps and clusters. 4. Shape = Distribution pattern with data B. Summarizing
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CAPM essay In the second scenario BBBY would use its $400 million in excess cash and borrow the remaining funds until Question 2 a) We will need to calculate the debt-to GDP ratio for each year separately in order to compute the total accumulation. The following equations and variables are used in question a) Year 1 Year 2 Year 3 Year 4 Year 5 Therefore‚ after 5 years the debt-to-GDP ratio will be equal to 104‚8 % (rounded to one decimal) b) The
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summaries are used for numeric data or for qualitative data. 2. Construct a frequency table‚ bar graph and pie chart for qualitative data. 3. Convert raw data into a data array. 4. Construct frequency table‚ relative and cumulative frequency tables‚ histogram‚ and ogive for quantitative data. 5. Construct a stem-and-leaf display to represent quantitative data. A. Summarizing Qualitative Data (2.1) 1. Introduction: Data are usually collected‚ entered‚ and saved into some form of database.
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