|BUSINESS STATISTICS | |FIRST INTERM EXAM | |COURSE: STAT201 TIME: 2 Hours | |DIRECTIONS: Answer questions
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Department of Management Faculty of Management and Human Resource Development SUBJECT: SHD 1713: STATISTIC 1 LECTURER: DR‚ LOW HOCK HENG PREPARED BY: NOOR AZNEE BINTI JUNAIDI ZULFADLY BIN SAIFUL MOHD RASYDUDDIN BIN MAT NAWI MOHD HAZRUL AZEWAN MOHD ASRI BIN MOHD ARIFIN MOHD FAKERRYIKMAL BIN KAMALUDIN 820423-12-5184 870314-56-5549 830503-03-5829 810406-01-5451 750203-08-5159 890417-59-5265 SX110698HDS04 SX110718HDS04 SX110686HDS04 SX105341HDD04 SX112315HDF04 SX112317HDF04 1. A researcher
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STUDENT PERFORMANCE DETERMINANTS IN A BUSINESS STATISTICS COURSE AT A LARGE URBAN INSTITUTION CIS 3300 November 30‚ 2012 INTRODUCTION This research paper discusses the effects of several different factors on a student’s success in a Business Statistics course. The different variables include areas related to the student’s academic factors as well as factors related to the student’s personal life. The academic related variables are: course of study‚ study hours per week‚ semester credit
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that would answer particular questions on a Likert scale of ten points‚ we would be able to measure and therefore treat the variables as interval variable so that we can statistically analyze our data. According to (Miles‚ 2010 pp. 8)‚ asking for a subjective evaluation of a particular element may render the measurement as ordinal rather than interval‚ we would address this challenge by creating defined criteria’s where we can evaluate the answers given against guidelines and reject answers that would
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distribution function for 100 normal random numbers. The K-S test is based on the maximum distance between these two curves. Characteristics and Limitations of the K-S TestAn attractive feature of this test is that the distribution of the K-S test statistic itself does not depend on the underlying cumulative distribution function being tested. Another advantage is that it is an exact test (the chi-square goodness-of-fit test depends on an adequate sample size for the approximations to be valid). Despite
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Normal(88.532‚5.07943) Normal(97.1033‚5.04488) Normal(107.15‚5.15367) Summary Statistics Mean 88.532 Std Dev 5.0794269 Std Err Mean 0.2271589 Upper 95% Mean 88.978306 Lower 95% Mean 88.085694 N 500 Sum 44266 Summary Statistics Mean 97.103333 Std Dev 5.0448811 Std Err Mean 0.2912663 Upper 95% Mean 97.676525 Lower 95% Mean 96.530142 N 300 Sum 29131 Summary Statistics Mean 107.15 Std Dev 5.1536687 Std Err Mean
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Major Statistics Assignment Mary Grace Rivero 050853639 CNUR860-011 Vaska Micevski Friday‚ March 30‚ 2012 Major Statistics Assignment This major statistics assignment will finally pull together everything that was learned in this course. The application of all content within this course will be incorporated to three different research scenarios. Within each scenario‚ hypothesis testing will be done‚ followed by a discussion of relevant descriptive statistics and finally‚ a discussion
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Scatterplots 4 Pearson’s Correlation 4 Spearman’s Rho 4 Probability 4 Binomial Distribution 4 Assumptions: 5 Subjective Probability 5 Normal Distribution 5 Standard Normal Distribution 5 Sampling Distribution 5 Standard Error of Statistic 5 Central Limit Theorem 5 Area under the Sampling Distribution of the Mean 6 Sampling Distribution‚ Difference between Independent means 6 Sampling Distribution of a Linear Combination of Means 6 Sampling Distribution of Pearson’s R 7
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Trajico‚ Maria Liticia D. BSEd III-A2 REFLECTION The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers‚ for example information about the number of times something happens. As I examined on what
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Millar Biology statistics made simple using Excel Biology statistics made simple using Excel Neil Millar Spreadsheet programs such as Microsoft Excel can transform the use of statistics in A-level science Statistics is an area that most A-level biology students (and their teachers!) find difficult. The formulae are often complicated‚ the calculations tedious‚ degrees of freedom mysterious‚ and probability tables confusing. But in fact students need no longer grapple with any of these.
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