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    Statistical Analysis BU 510 601 2 Credit Hours Fall 2013 Instructor: Shrikant Panwalkar Office phone: (410) 234 9456 Office Hours: By appointment panwalkar@jhu.edu Required Text and Learning Materials Business Statistics in Practice; 6th Edition‚ McGraw-Hill Higher Education‚ ISBN-13 978-0-07-340183-6 (There are other ISBN numbers) Authors: Bowerman‚ Bruce; O’Connell‚ Richard. (the cover shows a third author – Murphree) Please note: 7th edition is available‚ however

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    Session Number: _______________________ The following question will appear on your final exam. If you mark the box with either a or ‚ your midterm score will not be used in grade calculation. If the box is left blank‚ midterm score will be counted. EXAM Rules: This is an open-book‚ open-notes exam. Please leave your cell phone in your locker during the final exam on 10/10 (11am-3pm). PART I. MULTIPLE CHOICES 1. Circle your answers on the exam. 2. Copy

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    summaries: sleep “mening over prijs’ in variable; ok gemakkelijk om betekenis van variabele te gaan weergeven Crtl A : alles toevoegen. * Frequentietabel maken: analyze; descriptive statistics; frequencies * Median berekenen van mening over prijs: terug naar frequencies en display uitschakelen; statistics klikken en median aanklikken * Met tabel: charts aanklikken… * Beoordelingscijfer: er zit een fout in‚ nul = geen mening tonen aan SPSS dat dit een ontbrekende waarde is

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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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    the slope for X3 is 1.8232. The R2-value is 0.933 and the mean square error is 27.575. The final predictor entered is X4. The estimated intercept is -124.20‚ the estimated slope for X4 is 0.5174‚ the slope for X1 adjusts to 0.2963 and the slope for X3 adjusts to 1.357. The R2-value is 0.9615 and the mean square error is 16.581. Predictor X2 is not eligible for entry into the stepwise model because its t-test P-value doesn’t meet the 0.05 significance level. We prefer the model containing the three

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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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    Parameter Sample Random Bias Statistic Types of Variables   Graphs Measurement scales Nominal Ordinal Interval Ratio Qualitative Quantitative Independent Dependent   Bar Graph Histogram Box plot Scatterplot Measures of Center Spread Shape Mean Median Mode Range Variance Standard deviation Skewness Kurtosis Tests of Association   Inference Correlation Regression Slope y-intercept Central Limit Theorem Chi-Square t-test Independent samples Correlated samples

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    Statistics should be interpreted with caution as they can be misleading; they can both lie and tell the truth” Statistics are being used everyday to describe things in working and studying areas to show the productivity of the results they are hoping for. Therefore‚ people observe and notice alternative objects the world around. Throughout this fact‚ similarities and differences are such features that could endanger or turned out as advantages. This is called statistics. Explanations

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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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    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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