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Definition: The Sampling Distribution of Proportion measures the proportion of success, i.e. a chance of occurrence of certain events, by dividing the number of successes i.e. chances by the sample size ’n’. Thus, the sample proportion is defined as p = x/n. The sampling distribution of proportion obeys the binomial probability law if the random sample of ‘n’ is obtained … [Read more...] about Sampling Distribution of Proportion

Definition: The Sampling Distribution of the Difference between Two Means shows the distribution of means of two samples drawn from the two independent populations, such that the difference between the population means can possibly be evaluated by the difference between the sample means. Let say, there are two populations, first of size N1, with mean ?1, and standard … [Read more...] about Sampling Distribution of the Difference Between Two Means

Definition: The Sampling Distribution of Median shows the distribution of sample medians, a mid-value in the items arranged in some chronological order in the sample drawn from the population. If the population is large approximated by the normal distribution with mean? And a standard deviation σ, the medians of random samples of size n are distributed with mean? And a … [Read more...] about Sampling Distribution of Median

Definition: The Sampling Distribution of the Mean is the mean of the population from where the items are sampled. If the population distribution is normal, then the sampling distribution of the mean is likely to be normal for the samples of all sizes. Following are the main properties of the sampling distribution of the mean: Its mean is equal to the population mean, … [Read more...] about Sampling Distribution of Mean

Definition: The Sampling Distribution helps in determining the degree to which the sample means from different samples differ from each other, and the population mean to determine the degree of closeness between the particular sample mean to the population mean. In other words, the sampling distribution constitutes the theoretical basis of inferential statistics that … [Read more...] about Sampling Distribution

Definition: The Sample is the representative of the population from where it is drawn, and thus the Sample Distribution measures the frequency with which the number of subjects that make up the sample is actually drawn for a given research study. The samples are drawn when the population size is large, and it is not possible for an investigator to completely enumerate all … [Read more...] about Sample Distribution

Definition: The Population Distribution is a form of probability distribution that measures the frequency with which the items or variables that make up the population are drawn or expected to be drawn for a given research study. The characteristics or attributes of the population, i.e. the value of each variable in the population can be determined only when the investigator … [Read more...] about Population Distribution

Definition: The Central Limit Theorem states that when a large number of simple random samples are selected from the population and the mean is calculated for each then the distribution of these sample means will assume the normal probability distribution. In other words, the sample means will be normally distributed when the mean and standard deviation of the population is … [Read more...] about Central Limit Theorem

Definition: The Non-Sampling Error is the statistical error that arises due to the factors other than the ones that occur when the inference is drawn from the sample. Simply, the errors caused due to the defective methods of data collection, faulty definition, incomplete population coverage, wrong tabulations, etc. when the complete enumeration of all the items in the … [Read more...] about Non-Sampling Error

Definition: The Sampling Error refers to the statistical error occurred when the subset of the population (sample) deviates from the true characteristics, attributes and behavior of the total population. Simply, when the sample selected from the population differs from the actual attributes of the target population, then the sampling error arises. Basically, there are two … [Read more...] about Sampling Error