The physically impossibility of checking all the items in the population C. The adequacy of sample results D. All the above are reasons for sampling 5. Which of the following types of samples can you use if you want to make valid statistical inferences from a sample to a population? A. A judgment sample B. A quota sample C. A convenience sample D. A probability sample 6.
2.12 b. 1.734 c. -1.740 d. 1.740 ANSWER: d -same process but now go to one tailed α=0.05 and dof = 17 4. Read the t statistic from the table of t distributions and circle the correct answer. A one-tailed test (lower tail), a sample size of 10 at a .10 level of significance; t = a. 1.383 b.
Since the parameter is a population mean of a continuous variable variable, this suggests a one sample test of a mean. 2. SPECIFY THE NULL AND ALTERNATIVE HYPOTHESES. The second step is to state the research question in terms of a null hypothesis (H0) and a alternative hypothesis (HA). The null hypothesis is the population parameter, µ = $30,000 (H0: µ = $30,000).
Review Questions - 2: MGMT 3101 (For Final Exam) Section I: (True or False) 1. Hypothesis testing is a procedure based on sample evidence and probability theory used to decide whether the hypothesis is a reasonable statement and should be not be rejected or is unreasonable and should be rejected. 2. An alternate hypothesis is a statement about a population parameter that is accepted when the null hypothesis is rejected. 3.
Since this correlation is the test retest you can obtain considerable different estimates depending on the time gap. The next is parallel form you first have to create two parallel forms. One way to accomplish this is to create large sets of questions which address the same subject and then randomly divide the questions into two sets. You give both sets of questions to the same people. The correlation between the two parallel forms is the estimate of reliability.
Dimensionally all regions become sparse in density model. The sparsity behavior in high dimensionality makes all points look very similar to one another and the observation is true and these outliers may be discovered by examining the distribution of the data in a lower dimensional local subspace [2].Low dimensional subspace contains outlier and the character is latent to analysis. This is the combinational process of clustering and regression. To show the outlier pattern analysis and subspace analysis high dimensional model is determined. This can be a huge challenge to compute the high dimensional data because the simultaneous discovery of relevant data localities and subspaces is very difficult [2].High-dimensional methods provide an interesting direction for intentional understanding of outlier analysis when the subspaces are described in terms of the original attributes
3.5.1 Sampling According to Saunders, Lewis, & Thornhill (2009) sampling techniques incorporate variety of methods that reduce the amount of data needed to collect, by means of studying only data from a sub-group opposed to all possible cases or elements. Moreover, sampling is appropriate when different constraints to collect data for entire population exist, such as time or resources. Finally, the smaller amount of data means more time and resources left for reaching higher accuracy and detailed analysis. Due to the fact that our study is time limited and the results must be delivered quickly, we have selected the most suitable sampling method that would enable detailed analysis and bring high quality results. The suitability of the sampling
One way to do this is by narrowly defining the sampling criteria to make the sample as homogeneous (or similar) as possible to control for extraneous variables. Other methods include randomization or random assignment of subjects to groups; matching subjects on extraneous variables and then assigning them randomly to groups; application of statistical techniques of analysis of covariance; and balancing means and standard deviations of groups (Mcleod, 2008). The amount of control that the researcher has over the variables being studied varies, from very little in exploratory studies to a great deal in experimental design, but the limitations on control must be addressed in any research proposal (Silverstein,
Underlying assumptions. * The population values for each cluster is normally distributed. * The subjects are selected based on simple random technique. * The samples are measured according to the number of samples of observations in that sample * The sample cluster is typically human participants. Null and alternative hypothesis.
An advantage of a survey is that you can get lots of data in a relatively short space of time and a disadvantage is that the responses may not always be specific. The most common form of qualitative research is face to face interview which is basically a meeting with someone to discuss various issues. Quantitative data is data that is usually in the form of numerical or statistical data while qualitative data is a categorical measurement expressed not in the terms of numbers but rather by a means of a natural language description. One way to acquire quantitative data is surveys while participant and non participant observations , case studies and unstructured interviews to get qualitative data. If the researcher decides to use any of the quantitative research method , they should always consider the size, cost and the purpose of the research whereas with the qualitative, they should take into