Disadvantages Requires selection of relevant stratification variables which can be difficult. With degrees of freedom equal to n - 1, the df are Finally, in some cases such as designs with a large number of strata, or those with a specified minimum sample size per groupstratified sampling can potentially require a larger sample than would other methods although in most cases, the required sample size would be no larger than would be required for simple random sampling.
For example, Joseph Jagger studied the behaviour of roulette wheels at a casino in Monte Carloand used this to identify a biased wheel. In this case, the batch is the population.
Next, we can calculate the test statistic. From the t-table and since test is right-tailed, we want as critical value the t-value with 0. A student from this group is selected randomly.
In general, if the null value falls within the confidence interval we fail to reject the null hypothesis. For example, in an opinion pollpossible sampling frames include an electoral register and a telephone directory. These t-values correspond to right-tail probabilities of 0.
Information about the relationship between sample and population is limited, making it difficult to extrapolate from the sample to the population. Similar considerations arise when taking repeated measurements of some physical characteristic such as the electrical conductivity of copper.
Since 39 is not on the table we will use the closest without exceeding which is That is, do you think 11 minutes is really that much different from 10 minutes? This situation often arises when we seek knowledge about the cause system of which the observed population is an outcome.
Statistical significance is concerned with whether an observed effect is due to chance and practical significance means that the observed effect is large enough to be useful in the real world. Hence, because the selection of elements is nonrandom, nonprobability sampling does not allow the estimation of sampling errors.
Systematic and stratified techniques attempt to overcome this problem by "using information about the population" to choose a more "representative" sample.
However, systematic sampling is especially vulnerable to periodicities in the list. The PPS approach can improve accuracy for a given sample size by concentrating sample on large elements that have the greatest impact on population estimates.
Statistical and Practical Significances Our decision in this last example was to reject the null hypothesis and conclude that the average wait time exceeds 10 minutes.
Words of Caution Critics of hypothesis-testing procedures have observed that a population mean is rarely exactly equal to the value in the null hypothesis and hence, by obtaining a large enough sample, virtually any null hypothesis can be rejected.
When we specify our hypotheses, we should have some idea of what size Type I error we can tolerate.
However, this has the drawback of variable sample size, and different portions of the population may still be over- or under-represented due to chance variation in selections.
Systematic sampling A visual representation of selecting a random sample using the systematic sampling technique Systematic sampling also known as interval sampling relies on arranging the study population according to some ordering scheme and then selecting elements at regular intervals through that ordered list.
SRS may also be cumbersome and tedious when sampling from an unusually large target population. Implementation usually follows a simple random sample. Second, utilizing a stratified sampling method can lead to more efficient statistical estimates provided that strata are selected based upon relevance to the criterion in question, instead of availability of the samples.
It is easy to implement and the stratification induced can make it efficient, if the variable by which the list is ordered Statistics problem sample correlated with the variable of interest.
Another drawback of systematic sampling is that even in scenarios where it is more accurate than SRS, its theoretical properties make it difficult to quantify that accuracy. A secondary use of confidence intervals is to support decisions in hypothesis testing, especially when the test is two-tailed.
Time spent in making the sampled population and population of concern precise is often well spent, because it raises many issues, ambiguities and questions that would otherwise have been overlooked at this stage. Where voting is not compulsory, there is no way to identify which people will actually vote at a forthcoming election in advance of the election.
If 15 have high blood pressure and 25 have high level of cholesterol, a how many people have high blood pressure and a high level of cholesterol? It is important that the starting point is not automatically the first in the list, but is instead randomly chosen from within the first to the kth element in the list.Learn statistics and probability for free—everything you'd want to know about descriptive and inferential statistics.
Full curriculum of exercises and videos. Actively solving practice problems is essential for learning probability. Strategic practice problems are organized by concept, to test and reinforce understanding of that concept.
Homework problems usually do not say which concepts are involved, and often require combining several concepts. Each of the Strategic Practice documents here contains a set of strategic practice problems.
In this section we present a collection of solved statistics problem, with fairly complete solutions. Ideally you can use these problems to practice any statistics subject that you are in need of, for any practicing purpose, such as stats homework or tests.
The collection contains solved statistic problems of various different areas in statistics, such. A probability sample is a sample in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined.
The combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their. Statistics Problems. Use the dropdown text boxes to describe the problem you want to review.
Then, click the Submit button. Statistics Problems With Solutions Return to Statistics Internet Library for videos, software assistance, more problems and review Part I Practice Problems on Descriptive Statistics Part II Practice Problems on Probability Part III.Download