Assignment Name: Weekly Summary 7.1 Course Name and Number: Data Analytics CBSC520 Abstract As written by S. Christian Albright and Wayne L. Winston, in this chapter we would discuss about concepts In Hypotheses testing, null and alternate hypotheses one-tailed versus two-tailed tests, types of errors, significance level and rejection region, significance from p-values, Hypotheses tests […]
1. Discuss the advantages of constructing a relative frequency distribution as opposed to a frequency distribution. A frequency distribution gives the number of observations or counts that fall in a particular category. The frequencies can be any whole number from 0 to infinity. On the other hand, a relative frequency distribution gives the proportion of observations
1. Discuss what is meant by classical probability assessment and indicate why classical assessment is not often used in business applications. The classical probability assessment method is one in which we define an experiment and an event of interest. Then, we find out the total number of possible outcomes of the experiment where each outcome
Case Study 2.1 – Assessment of Supply chain efficiency by DEA University of the Potomac CBSC-520 Abstract Conduct a study on the assessment paper of hardwood sawmills prepared using Data Envelopment Analysis (DEA) to identify supply chain inefficiencies when hardwood sawmills were under severe financial pressure. The New York state had about 175 hardwood sawmills
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Weekly Summary 4.1 Course Title: CBSC520 Data Analytics University of the Potomac Abstract In this paper we discussed about what we have learned in this week and following is a summary of what we understood. This week class depicts the topics of what is Normal distribution, Binomial distribution, Exponential distribution and Poisson distribution? The normal
Assignment Name: Weekly Summary 5.1 Course Name and Number: Data Analytics CBSC 520 Abstract As written by S. Christian Albright and Wayne L. Winston, in this chapter we would discuss about Probability and probability essentials. We also discuss about elements of decision analysis, Identifying the problems, possible outcomes, Decision trees, One-stage decision problems, Precision tree
Sampling and Sampling Distributions WS 6.1 CBSC520.17 Weekly Summary 6.1 This week we learned two chapters. One was about Sampling and Sampling Distribution and the other on Confidence Interval Estimation. In this summary, we see what the concepts in these chapters help us learn. In Chapter 7, Sampling and Sampling Distribution, we how different types
Weekly Summary 1.1 University of Potomac CBSC520.18 Weekly Summary 1.1 This week was the first week of class. We learned the basics of Data analysis. We see how Technology has advanced and many businesses depend on information systems for their growth. It is because of information systems, that data can be collected and analysis can
Weekly Summary 2.1 CBSC520.18 Weekly Summary 2.1 This week is the second week of class. This week, in chapter three, we learned about finding relationships among variables. We see that relationship between variables is the primary thing of interest that we need for data analysis. Examining relationships between categorical variables, the count of categories is
Weekly Summary 3.1 University of the Potomac Data Analytics CBSC 520 Weekly Summary 3.1 In this week, I learned the topics about Probability Essentials like Addition rule, Conditional Probability and Multiplication rule, Equally Likely Events, Probability Distribution of a single variable, Summary Measures of a Probability Distribution, Conditional Mean and Variance and Introduction to Simulation. The addition