M&M Report Alex Colbert Strayer University Abstract Statistics is not an easy topic for your everyday person to pick up and make it easy for them to understand. Equations and hypothesis and the like can be overwhelming and confusing. But what about when you relate it to something that is common in everyday life? Throughout the semester we were given the task to evaluate M&Ms in a few different statistical ways. Throughout this report the goal is to be able to explain what happened‚ and offer
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|THE ROLE OF MATHEMATICAL SCIENCES IN CENSUS. | | | |A CASE STUDY OF NIGERIA | | | |2/21/2012
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1. Rainfall 1.1. Use appropriate descriptive graphical and numerical summaries to describe the main features of the annual and seasonal rainfalls and their overall distributions 1.1.1. Graphical presentation of the main features of the annual and seasonal rainfalls: Fig.1: Multiple Bar Charts Fig 2: Line Chart These graphs show that there is maximum Annual Rain and Monsoon Rain at station Lumle ID number 17. Their distribution approaches to approximately normal. These graphs shows
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studied was not influenced by the researcher themselves. 3. In the following scenario what is the statistic and the parameter (population as a whole) it would estimate. A recent study of 460 drivers age 70 and over by the National Highway Traffic Safety Administration reported that 75% of those drivers had uncorrected vision problems. my answer: 75% (345 people) was the reported statistic from the 460 drivers of 70 or older drivers. my answer: The assumed parameter would be the population
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estimates get more precise and accurate. ================================================================ SPSS: Confidence Intervals This procedure finds statistics about a single variable from a sample‚ and estimates confidence intervals for the variable. 1. Menu bar‚ Analyze‚ Descriptive Statistics‚ Explore Opens the “Explore” Box Variable list on left Three working areas in the middle Ignore the second and third Option buttons on the right A “Display” area underneath
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University of Perpetual Help System Dalta Molino Campus Molino III‚ Bacoor City Probability and Statistics LAGERA‚ Einar John A. Table of Contents Simple Correlation Analysis ................................................................................................. 1 Introduction .................................................................................................................................................................. 1 What is Correlation? ...........
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Table of Contents Frequencies: Statistics RESPONDED GENDER HSC GPA STUDY HOUR N Valid 75 75 75 Missing 0 0 0 Mean 1.51 4.8520 4.5600 Median 1.51a 4.9442a 4.5094a Mode 2 5.00 4.00 Std. Deviation .503 .23673 1.00324 Variance .253 .056 1.006 Skewness -.027 -1.608 .408 Std. Error of Skewness .277 .277 .277 Kurtosis -2.055 1.864 -.117 Std. Error of Kurtosis .548 .548 .548 Range 1 1.00 4.00 Sum 113 363.90 342.00 Percentiles
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1. Introduction: Job satisfaction describes how content an individual is with his or her job. It is a relatively recent term since in previous centuries the jobs available to a particular person were often predetermined by the occupation of that person’s parent. There are a variety of factors that can influence a person’s level of job satisfaction. Some of these factors include the level of pay and benefits‚ the perceived fairness of the promotion
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ANSWER: a 4. One-tailed alternatives are phrased in terms of: a. ( b. < or > c. ( or = d. [pic] ANSWER: b 5. The chi-square goodness-of-fit test can be used to test for: a. significance of sample statistics b. difference between population means c. normality d. probability ANSWER: c 6. A type II error occurs when: a. the null hypothesis is incorrectly accepted when it is false b. the null hypothesis is incorrectly
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Statistics with Ms Excel Simple Statistics with Excel and Minitab Elementary Concepts in Statistics Multiple Regression ANOVA Elementary Concepts in Statistics Overview of Elementary Concepts in Statistics. In this introduction‚ we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods
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