Sample Size and Confidence Interval

Hello everyone good morning / good afternoon.
Today I will discuss the sample size, different techniques of sample size and the confidence
interval.
Slide 1: In this slide I am going to discuss the sample size. The sample size determination is
basically the act for choosing the numbers of replicates or observations for including in a
statistical sample. The sample size is one of the most important features of any of the
empirical studies in that the goal is for making the inferences that are about a population from
a sample.
Slide 2: There are several sampling techniques. From them I have chosen Purposive
sampling, Random sampling and simple random sampling to discuss in this slide.
Purposive Sampling: In this technique, the units of the sampling can be selected according to
the purpose.
Random Sampling: In this technique, each of the units that are included in the sample, will be
having several pre-assigned chances of the inclusion into the sample.
Simple Random Sampling: This method provides the better and unbiased estimate of the
parameters, whether the population is homogeneous.
Slide 3: This is the example of the sample size calculator.
Slide 4: In this slide I am going to discuss the confidence interval. the Confidence Interval is
the type of the estimated intervals that can be computed from the statistics of the data that are
observed, which can contain the actual value of one population parameter that is unknown.
The confidence intervals can consist of the range of the values that are potential for the
population parameters that are unknown.
Slide 5: The point estimation can involve the utilization of the sample data for calculating a
single value that is for serving as s ‘best estimate’ or ‘best guess’ of a population parameter
that is unknown. The point estimation is able to be contrasted with the interval estimation.
The interval estimates are credible interval or the confidence intervals.
Slide 6: In this slide I am going to discuss the Standard error. In statistics, the standard error
is the deviation that is standard for the sampling distribution of it or an estimation of the
deviation that is standard. The relation between the standard deviation and standard error is,