Simply use statistics as a tool. You will be given a data. (Next year you will not be given data‚ you will gather data yoruself). 1. Data: one of the variables is dependent and other dependent. Can be multiple. Then do regression analysis. ANOVA for overall significance and Regression equation. And write based on ANOVA there is a significance or not. 2. Some comments on correlation: volume vs. horse power etc. 3. Hypothesis test of one population. I assume that the mean is etc etc. Small paragraph
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and to make it as relatable and as descriptive as possible. One of the tools used was a meter In poetry‚ meter is the basic rhythmic structure of a verse or lines in verse. Many traditional verse forms prescribe a specific verse metre‚ or a certain set of metres alternating in a particular order. They also used Repetition of a sound‚ syllable‚ word‚ phrase‚ line‚ stanza‚ or metrical pattern which is a basic unifying device in all poetry the writer is usually trying to express an emotion or a phrase
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a set is a collection of distinct objects‚ considered as an object in its own right. For example‚ the numbers 2‚ 4‚ and 6 are distinct objects when considered separately‚ but when they are considered collectively they form a single set of size three‚ written {2‚4‚6}. an element‚ or member‚ of a set is any one of the distinct objects that make up that set A number‚ letter‚ point‚ line‚ or any other object contained in a set. There are two ways of describing‚ or specifying the members
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| 70 | 29 | E | 22 | 6 | F | 27 | 15 | G | 28 | 17 | H | 47 | 20 | I | 14 | 12 | J | 68 | 29 | | | | | | | a) draw a scatter diagram of number of sales calls and number of units sold b) Estimate a simple linear regression model to explain the relationship between number of sales calls and number of units sold y=2.139x-1.760 Number of units sold=2.139Number of units sold-1.760 c) Calculate and interpret the coefficient of correlation r=0.853=0.9236 (There
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IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
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relationship between CREDIT BALANCE and SIZE 2591+ 403.221 Determine the coefficient of correlation. Interpret. .75/ r-sq(56.6%). There is a mild correlation. Determine the coefficient of determination. Interpret. 56.6% Test the utility of this regression model (use a two tail test with α =.05). Interpret your results‚ including the p-value. P-value=0. Reject the null hpothesis. T value 7.9147 Based on your findings in 1-5‚ what is your opinion about using SIZE to predict CREDIT BALANCE? Size
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features but some negative aspects also exist. This paper describes the concept of privacy in Online Social Network. First‚ various privacy threats are explored and brief description of these threats is provided. Then‚ different models‚ related to the management and detection of privacy issues are explored and a tool for the detection of privacy violation is also discussed. Keywords: Online Social Networking (OSN)‚ privacy‚ threats‚ Trust evaluation‚ Data reachability model‚ PROTOSS‚ encryption‚ malware
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Censored data & Truncated data Censoring occurs when an observation or a measurement is outside the range and people don’ t know the certain value. The value is always above or below the range that people set. However‚ truncated data means that because of the limits‚ such as time‚ or space‚ people lose some data. Truncation is to cut off the data. In other words‚ we have collected and use the data‚ but the data is not in the range we have. It is called censored data. We don’t use the data because
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Problem Set 4 Complete all questions listed below. Clearly label your answers. 1. What determines whether a financial asset is included in the M1 money supply? Why are interest-earning checkable deposits included in M1‚ whereas interest-earning savings accounts and Treasury bills are not? If the financial asset can be turned into real money fast. Intrest earning checkable deposits are included because they can be converted quickly into paper money. Intrest earning savings accounts and treasury
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Mutually agreed between historians‚ the 19th century was a time period of rapid and significant European upheaval and progression in terms of society‚ politics‚ science and economy. The European Powers‚ including Germany and Great Britain‚ not only were the dominating forces on the continent but were also already the most powerful nations in the world. No other continent in this time period contained such influential and well-developed nations that were able to successfully control trade around
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