Publications by Laboratory Exercise No. 5
Stat 142 Lesson 1.2 (Components of a time series)
1 Introduction Patterns in time series data are the backbone of the analysis of it. As with other fields of statistics and, in particular, the field of machine learning, one of the primary goals of time series analysis is to identify patterns in data. Those patterns can then be utilized to provide meaningful insights about both past and future ...
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Stat 136 Lesson 1.1 (Main Approaches to Statistics)
The Scientific Method: A Process for Learning In the Middle Ages, science was deduced from principles set down many centuries earlier by authorities such as Aristotle. The idea that scientific theories should be tested against real world data revolutionized thinking. This way of thinking known as the scientific method sparked the Renaissance. T...
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Stat 136 Lesson 1.2 (The Bayes Theorem)
Conditional Probability and Law of Total Probability Recall that by definition, the conditional probability of A given B, is \[ P(A|B) = \frac{P(A \cap B)}{P(B)}, \text{provided} \; P(B)>0. \tag{1} \] Similarly, we have \[ P(B|A) = \frac{P(A \cap B)}{P(A)}, \text{provided} \; P(A)>0. \tag{2} \] By multiplication, we obtain from (2), \[ P(A \c...
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Stat 221- Correlation Analysis
Learning Objectives Identify the most appropriate measure of correlation/association, Compute measures of correlation/association using JASP,and Interpret results of correlation analyses Basic ideas Correlation analysis is a statistical technique used to determine the degree of linear relationship between two or more variables It is a meth...
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Stat 221- Linear Regression Analysis
Motivation In correlation analysis, we are able to say that one variable is linearly related to another Correlation does not imply causation As the value of one variable increases (decreases), so does the value of the other variable We avoid to use the term dependent and independent to refer to the variables in a correlation analysis How much...
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Stat 141- Problem Set No. 5
INSTRUCTIONS: Write your solutions in RMarkdown. Submit as pdf or html. If you used html format, publish your html document in Rpubs.com and attach the link of your file in the VSUEE assignment. Problem No.1 The surface finish of metal parts made on four randomly selected machines is being studied. An experiment is conducted in which each ma...
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Stat 141 Analysis of Covariance
Quick review Nuisance factor- factor that may have an effect on the response variable but of not an interest to the researcher Unknown and uncontrollable- randomization balances out its impact across the experiment Known and controllable- blocking or grouping of the experimental units using the nuisance factor as grouping variable Known but...
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Stat 141- ANSWER KEY (Problem Set No. 4)
INSTRUCTIONS: Write your solutions in RMarkdown. Submit as pdf or html. If you used html format, publish your html document in Rpubs.com and attach the link of your file in the VSUEE assignment. Problem No.1 Derive the expected mean squares of a three-factor factorial experiment where factors A and B are random and C is fixed. SOLUTION: R ...
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Stat 141 Split-Plot Experiments
Basic ideas a two-factor experiment wherein levels of one of the factors require large plot size for execution and also show large differences in their effects the experiment will consist of a set of large plots called main plots in which levels for the main plot factor are assigned each main plot is divided into subplots to which the secon...
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Stat 141 Experiments with Nested Factors
Nested (hierarchical) factors Recall that in a factorial experiment, the levels of factor A are “crossed” with the levels of factor B In some two-factor experiments the level of one factor , say B, is not “cross” or “cross classified” with the other factor, say A, but is “NESTED” with it. Nesting may occur in the treatment str...
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