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What skills and competencies are tested in the Statistics part of Subtest II?
The following are concepts and associated skills you ought to master to do well on the Subtest II: Statistics section.
1. Describe Univariate Data: Be able to calculate, interpret and apply the properties of the measures of central tendency and dispersion of a data set. In particular, determine the mean, median mode, standard deviation and variance of a sample, especially in Class Interval form; know how each of them is changed when the data is transformed ie. a constant is added/multipled to each datum; depending on the skewness of the distribution, know which measure(s) to use to describe the data.
2. Describe Bivariate Data: Know the difference between Correlation and Regression; understand the assumptions underlying each and hence their applicability; be able to calculate and interpret the Correlation Coefficient, r, and the Least-Squares Regression Line (LSRL); know the properties of the Correlation Coefficient and the LSRL; possess a broad comprehension of the derivation of the LSRL - you don't need to be able to actually derive it but you need to know how the line came about (ie. the logic behind it); make predictions using the LSRL.
3. Methods of Generate Data: Possess a broad understanding of different ways of Producing Data and the Advantages (Benefits) and Disadvantages (Constraints) pertaining to each: Census; Surveys and their Designs; and types of Sampling Plans (Simple Random, Stratified, Systematic, Cluster, etc); Know the different kinds of Errors in performing Surveys (Response / Non-Response); Understand the means to control Sampling Variability
4. Apply Principles of Probability: Be able to apply the basic Rules of Probability; identify Dependent and Independent Events, Mutually Exclusive and Non-Disjoint Events and determine their probabilities; Have a firm grasp of conditional probability, especially using the Tree Diagram
5. Describe Common Distributions: Have a general knowledge of different kinds of distributions and their underlying assumptions and properties: Discrete (Binomial, Poisson) and Continuous (Uniform, Normal); Be able to identify the distribution pertaining to real-life situations; Be able to determine probablities concerning Binomial and Normal Distributions
6. Statistical Inference: Perform Tests of Hypothesis, in particular, the Chi-square Goodness of Fit test and the Chi-Square Test of Independence of 2 categorical variables; State the Hypothesis, check the underlying assumptions, perform the test, interpret the P-value and write conclusions.
Qs? Call (Jay): 951-489-7665
OR email me: [email protected].
The following are concepts and associated skills you ought to master to do well on the Subtest II: Statistics section.
1. Describe Univariate Data: Be able to calculate, interpret and apply the properties of the measures of central tendency and dispersion of a data set. In particular, determine the mean, median mode, standard deviation and variance of a sample, especially in Class Interval form; know how each of them is changed when the data is transformed ie. a constant is added/multipled to each datum; depending on the skewness of the distribution, know which measure(s) to use to describe the data.
2. Describe Bivariate Data: Know the difference between Correlation and Regression; understand the assumptions underlying each and hence their applicability; be able to calculate and interpret the Correlation Coefficient, r, and the Least-Squares Regression Line (LSRL); know the properties of the Correlation Coefficient and the LSRL; possess a broad comprehension of the derivation of the LSRL - you don't need to be able to actually derive it but you need to know how the line came about (ie. the logic behind it); make predictions using the LSRL.
3. Methods of Generate Data: Possess a broad understanding of different ways of Producing Data and the Advantages (Benefits) and Disadvantages (Constraints) pertaining to each: Census; Surveys and their Designs; and types of Sampling Plans (Simple Random, Stratified, Systematic, Cluster, etc); Know the different kinds of Errors in performing Surveys (Response / Non-Response); Understand the means to control Sampling Variability
4. Apply Principles of Probability: Be able to apply the basic Rules of Probability; identify Dependent and Independent Events, Mutually Exclusive and Non-Disjoint Events and determine their probabilities; Have a firm grasp of conditional probability, especially using the Tree Diagram
5. Describe Common Distributions: Have a general knowledge of different kinds of distributions and their underlying assumptions and properties: Discrete (Binomial, Poisson) and Continuous (Uniform, Normal); Be able to identify the distribution pertaining to real-life situations; Be able to determine probablities concerning Binomial and Normal Distributions
6. Statistical Inference: Perform Tests of Hypothesis, in particular, the Chi-square Goodness of Fit test and the Chi-Square Test of Independence of 2 categorical variables; State the Hypothesis, check the underlying assumptions, perform the test, interpret the P-value and write conclusions.
Qs? Call (Jay): 951-489-7665
OR email me: [email protected].