Buisness Statatis
Q. Explain the term Sampling distribution
The term sampling distribution refers to a frequency or probability distribution of the sample statistic obtained from all the possible samples of size n taken at random from a given population. The sample mean (x) shows the average value calculated from measurements of a sample.
Its main characteristics are:
1. The average of all sample means should equal to the true population mean (µ)
2. The standard deviation shows dispersion of sample means around the population mean. It is known as the standard error of the mean
3. The sampling distribution of the mean is a normal distribution.
Uses: The sampling distribution of the means is commonly analysed in statistical inferences, being useful in statistical estimation, hypotheses testing and statistical quality control.
Q. Explain what is meant by sampling distribution of proportions and its uses.
The sampling distribution of proportions is a probability distribution of the sample proportions. From a given population, all the possible samples of size n may be selected at random , each provides a sample proportion.
Uses: 1. For estimation of the unknown population proportion(π) using a sample proportion (p) based on confidence interval. 2. For hypothesis testing of a sample proportion or difference between two proportions.
Q. Differences between a paired comparison t test and an independent t test
A paired comparison t-test is used to determine if there is evidence of significant difference between the means from observations of dependent samples. For example, a sample of employees being observed for their average output before and after they were sent for training.
An independent t-test is used to determine if there is evidence of significant difference between the means from observations of two independent samples. For example, a sample of employees from the day shift and another sample of
The term sampling distribution refers to a frequency or probability distribution of the sample statistic obtained from all the possible samples of size n taken at random from a given population. The sample mean (x) shows the average value calculated from measurements of a sample.
Its main characteristics are:
1. The average of all sample means should equal to the true population mean (µ)
2. The standard deviation shows dispersion of sample means around the population mean. It is known as the standard error of the mean
3. The sampling distribution of the mean is a normal distribution.
Uses: The sampling distribution of the means is commonly analysed in statistical inferences, being useful in statistical estimation, hypotheses testing and statistical quality control.
Q. Explain what is meant by sampling distribution of proportions and its uses.
The sampling distribution of proportions is a probability distribution of the sample proportions. From a given population, all the possible samples of size n may be selected at random , each provides a sample proportion.
Uses: 1. For estimation of the unknown population proportion(π) using a sample proportion (p) based on confidence interval. 2. For hypothesis testing of a sample proportion or difference between two proportions.
Q. Differences between a paired comparison t test and an independent t test
A paired comparison t-test is used to determine if there is evidence of significant difference between the means from observations of dependent samples. For example, a sample of employees being observed for their average output before and after they were sent for training.
An independent t-test is used to determine if there is evidence of significant difference between the means from observations of two independent samples. For example, a sample of employees from the day shift and another sample of