Publications by Laboratory Exercise No. 5
Stat 136 Long Exam 2 (Part 3)
Stat 136 (Bayesian Statistics) Long Exam No. 2 (Part 3) Author Norberto E. Milla, Jr. Published April 23, 2023 Problem No. 1: The number of defects per 10 meters of cloth produced by a weaving machine has the Poisson distribution with mean \(\lambda\). You examine 100 meters of cloth produced by the machine and observe 71 defects. a) Your p...
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Econ 115s Lesson 2.2 Multiple Linear Regression (Inference)
Stat 115s (Introduction to Econometrics) Lesson 2.2- Multiple Linear Regression: Inference Author Norberto E. Milla, Jr. Published April 21, 2023 1 Sampling distributions of OLS estimators To make statistical inference (hypothesis tests, confidence intervals), in addition to expected values and variances we need to know the sampling distribu...
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Stat 142 Lab Exercise No. 3
Stat 142 (Time Series Analysis) Laboratory Exercise No. 3 The data set fancy (in the fma package) concerns the monthly sales figures of a shop which opened in January 1987 and sells gifts, souvenirs, and novelties. The shop is situated on the wharf at a beach resort town in Queensland, Australia. The sales volume varies with the seasonal populati...
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Econ 115s Lesson 3.1 (Qualitative Explanatory Variables in Regression Analysis)
Table of contents 1 Introduction 2 Single dummy independent variable 3 Creating dummy variables in R 4 Adding quantitative variables 5 More than one dummy variables 6 Allowing for different slopes Stat 115s (Introduction to Econometrics) Lesson 3.1- Qualitative Explanatory Variables in Regression Analysis Author Norberto E. Milla, Jr. P...
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Stat 142- Lesson 2.3 (Time series regression models)
Table of contents 1 Introduction 2 The linear model 2.1 Simple linear regression model 2.2 Multiple linear regression model 2.3 Assumptions 3 Least squares estimation 3.1 Example 3.2 Fitted values 3.3 Goodness-of-fit 4 Evaluating the regression model 4.1 ACF plot of residuals 4.2 Other useful plots of residuals 4.3 Outliers and i...
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Stat 136 Lab Exercise No. 4
INSTRUCTION: Provide details of all calculations. Problem 1 You are the statistician responsible for quality standards at a cheese factory. You want the probability that a randomly chosen block of cheese labelled “1 kg” is actually less than 1 kilogram to be 1% or less. The distribution of the weight (in grams) of blocks of cheese produce...
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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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