Statistical Methods(SM) chapter 8 9 and 10 exercise solution

Statistical Methods(SM) Anderson's Chapter 8, 9 and 10 Exercise solution.


Download Chapter 8 9 and 10 Solution


 Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)

Statistical Methods SM Exercise Solution

The students of GTU ( Gujarat Technological University) MCA 3rd semester has a subject Statistical Methods(SM) in syllabus the main reference book for SM is Anderson, Sweeney, Williams, “Statistics for business and economics”, 9th edition of Thompson Publication.

Here I provided the Anderson books exercise solution of Chapter 3, 4, 5, 6, 7 and 8.

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: GTU MCA Semester 3,Statistical Methods(SM)

Statistical Methods(SM) chapter 8 exercise solution

Statistical Methods(SM) Anderson's Chapter 8 Exercise solution.


Download Chapter 8 Interval Estimation exercise solution.


Learning Objectives

1. Know how to construct and interpret an interval estimate of a population mean and / or a population proportion.
2. Understand and be able to compute the margin of error.
3. Learn about the t distribution and its use in constructing an interval estimate for a population mean.
4. Be able to determine the size of a simple random sample necessary to estimate a population mean and/or a population proportion with a specified level of precision.
5. Know the definition of the following terms:
6. confidence interval margin of error
   confidence coefficient degrees of freedom
   confidence level

Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)

Statistical Methods(SM) chapter 7 exercise solution

Statistical Methods(SM) Anderson's Chapter 7 Exercise solution.

Download Chapter 7 Sampling and Sampling Distributions exercise solution.


Learning Objectives:

1. Understand the importance of sampling and how results from samples can be used to provide estimates of population characteristics such as the population mean, the population standard deviation and / or the population proportion.
2. Know what simple random sampling is and how simple random samples are selected.
3. Understand the concept of a sampling distribution.
4. Understand the central limit theorem and the important role it plays in sampling.
5. Specifically know the characteristics of the sampling distribution of the sample mean ( x ) and the sampling distribution of the sample proportion ( p ).
6. Learn about a variety of sampling methods including stratified random sampling, cluster sampling, systematic sampling, convenience sampling and judgment sampling.
7. Know the definition of the following terms:

• parameter sampling distribution
• sample statistic finite population correction factor
• simple random sampling standard error
• sampling without replacement central limit theorem
• sampling with replacement unbiased
• point estimator relative efficiency
• point estimate consistency

Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)

Statistical Methods(SM) chapter 6 exercise solution

Statistical Methods(SM) Anderson's Chapter 6 Exercise solution.


Download Chapter 6 Continuous Probability Distributions exercise solution 


Learning Objectives

1. Understand the difference between how probabilities are computed for discrete and continuous random variables.
2. Know how to compute probability values for a continuous uniform probability distribution and be able to compute the expected value and variance for such a distribution.
3. Be able to compute probabilities using a normal probability distribution. Understand the role of the standard normal distribution in this process.
4. Be able to use the normal distribution to approximate binomial probabilities.
5. Be able to compute probabilities using an exponential probability distribution.
6. Understand the relationship between the Poisson and exponential probability distributions.

Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)

Statistical Methods(SM) chapter 5 exercise solution

Statistical Methods(SM) Anderson's Chapter 5 Exercise solution.

Download Chapter 5 Discrete Probability Distributions exercise solution

Learning Objectives

1. Understand the concepts of a random variable and a probability distribution.
2. Be able to distinguish between discrete and continuous random variables.
3. Be able to compute and interpret the expected value, variance, and standard deviation for a discreteb random variable.
4. Be able to compute and work with probabilities involving a binomial probability distribution.
5. Be able to compute and work with probabilities involving a Poisson probability distribution.
6. Know when and how to use the hypergeometric probability distribution.

Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)

Statistical Methods(SM) chapter 4 exercise solution

Statistical Methods(SM) Anderson's Chapter 4 Exercise solution.

Download Chapter 4 Introduction to Probability exercise solution

Learning Objectives:

1. Obtain an appreciation of the role probability information plays in the decision making process.
2. Understand probability as a numerical measure of the likelihood of occurrence.
3. Know the three methods commonly used for assigning probabilities and understand when they should be used.
4. Know how to use the laws that are available for computing the probabilities of events.
5. Understand how new information can be used to revise initial (prior) probability estimates using Bayes’ theorem. 

Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)

Statistical Methods(SM) chapter 3 exercise solution

Statistical Methods(SM) Anderson's Chapter 3 Exercise solution.



Download Solution of Chapter 3 Descriptive Statistics: Numerical Methods

Learning objective of this Chapter is:

1. Understand the purpose of measures of location.
2. Be able to compute the mean, median, mode, quartiles, and various percentiles.
3. Understand the purpose of measures of variability.
4. Be able to compute the range, interquartile range, variance, standard deviation, and coefficient of
variation.
5. Understand skewness as a measure of the shape of a data distribution. Learn how to recognize when a
data distribution is negatively skewed, roughly symmetric, and positively skewed.
6. Understand how z scores are computed and how they are used as a measure of relative location of a
data value.
7. Know how Chebyshev’s theorem and the empirical rule can be used to determine the percentage of
the data within a specified number of standard deviations from the mean.
8. Learn how to construct a 5-number summary and a box plot.
9. Be able to compute and interpret covariance and correlation as measures of association between two
variables.
10. Be able to compute a weighted mean.

Download Solution of Chapter 3 Descriptive Statistics: Numerical Methods


Related Posts:

• Chapter 3 Descriptive Statistics: Numerical Methods
• Chapter 4 Introduction to Probability
• Chapter 5 Discrete Probability Distributions
• Chapter 6 Continuous Probability Distributions
• Chapter 7 Sampling and Sampling Distributions
• Chapter 8 Interval Estimation
• Chapter 9, 10

Read more »

Posted in: Statistical Methods(SM)