Publications by Laboratory Exercise No. 5
Stat 136 Lesson 3.1- Bayesian Inference on the Normal Mean
Table of contents Introduction: The Normal Distribution Bayes inference for the normal mean using discrete prior Example 1: Example 2: Bayes inference for the normal mean using continuous prior Jeffrey’s uniform prior for the normal mean Normal prior density for the normal mean Example 3: Choosing a normal prior Bayesian credible interval fo...
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Econ 115s Lesson 2.3 Further Topics in Linear Regression Analysis
Table of contents 1 Effects of Data Scaling on OLS Statistics 1.1 Examples 2 Standardized Regression 2.1 Example 3 More on logarithmic transformation 3.1 Some rules of thumb for taking logs 4 Quadratic models 4.1 Example 1 4.2 Example 2 5 Models with interaction terms 5.1 Example 6 Prediction 6.1 Example Stat 115s (Introdu...
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Stat 142 Lab Exercise No. 2
Read the retail.xlsx data into R. This data contains monthly retail sales of electronic goods and clothing from April 1984 to December 2009. Select the electronic goods data and convert it to a time series. Explore this series by plotting it using the autoplot() function. Can you spot any seasonality, cyclicity, or trend? What do you learn abo...
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Stat 136 Quiz No. 3
NAME: _____________________________________ SCORE: _______ Suppose you own a trucking company with a large fleet of trucks. Breakdowns occur randomly in time and the number of breakdowns during an interval of t days is assumed to be Poisson distributed with mean \(\lambda\). The parameter \(\lambda\) is the daily breakdown rate. The possible va...
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Stat 136 Lab Exercise No. 3
INSTRUCTION: Provide details of all calculations. Problem 1 The number of claims received by an insurance company during a week follows a Poisson(\(\lambda\)) distribution. The weekly number of claims observed over a ten week period are: 5, 8, 4, 6, 11, 6, 6, 5, 6, 4. Suppose a prior uniform distribution is used for \(\lambda\). Find the post...
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Data Visualization
Plotting One Variable Introduction To visualize one variable, the type of graphs to be used depends on the type of the variable: For categorical variable or grouping variables. You can visualize the count of categories using a bar plot or using a pie chart to show the proportion of each category. Dot charts can be another alternative. For con...
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Stat 142- Lesson 2.2 (Exponential Smoothing)
Table of contents 1 Introduction 2 Simple exponential smoothing 2.1 Example of SES implementation with fixed smoothing parameter 2.2 Example of SES implementation with optimal smoothing parameter 3 Holt’s linear trend method 3.1 An example 4 Damped trend methods 4.1 An example 4.2 One more example 5 Holt-Winters’ seasonal metho...
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Econ 115s Lesson 2.2- Multiple Linear Regression Model (Statistical Inference)
Table of contents 1 Sampling distribution of OLS estimators 2 Testing Hypotheses about a single population parameter: the t test 2.1 Some examples 3 Large standard errors, small t statistics, and confidence intervals 3.1 An example: Model of R&D expenditures 4 Testing Hypotheses about a single linear combination of the parameters 4.1 A...
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Sta 142 Long Exam No. 1 (Part 3)
Stat 142 (Time Series Analyis) Long Exam No. 1 (Part 3) Author Norberto E. Milla, Jr. Published March 23, 2023 Show algebraically that a \(3 \times 5\) moving average is the same as a 7-term moving weighted average with weights of 0.067, 0.133, 0.200, 0.200, 0.133, and 0.067. [5 points] The plastics data set in the fma package consists of th...
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Stat 136 Lesson 2.3 (Bayesian Inference for the Poisson Mean)
Table of contents Review: The Poisson Distribution Bayesian Inference for the Poisson Mean Using Discrete Prior Bayesian Inference for the Poisson Mean Using Continuous Prior An Example Stat 136 (Bayesian Statistics) Lesson 2.3: Bayesian Inference for the Poisson Mean Author Norberto E. Milla, Jr. Published March 23, 2023 Review: The Poiss...
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