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This comprehensive study guide covers essential quantitative research techniques and statistics for business students. Topics include sampling, inferential statistics, probability, central limit theorem, standard error, hypothesis testing, confidence level, and descriptive statistics. The guide also explains key concepts such as population, sample, statistical inference, parameter, statistic, and confidence level. It provides formulas, examples, and exercises to help students understand and apply these concepts.

Typology: Exams

2023/2024

1 / 6

Download Quantitative Research Techniques and Statistics Study Guide for Business Statistics 2024 and more Exams Nursing in PDF only on Docsity! Quantitative Research Techniques + Statistics – Peregrine Study Guide 2024 A company developed a smartphone whose average lifetime is unknown. In order to estimate the average, 200 smartphones are randomly selected from a large production line and tested; their average is found to be 5 years. The 200 smartphones represent: ✔ a sample Significance level ✔ Measures the reliability of a statistical inference inferential statistics ✔ Process of using sample statistics (mathematics) to draw conclusions about population parameters mutually exclusive ✔ Events that cannot occur at the same time. sampling error ✔ the difference between the results of random samples taken at the same time non-sampling error ✔ occurs when the sample data are incorrectly collected, recorded, or analyzed. Three types of errors: data acquisition errors, non-response errors (or bias), selection bias Design of a good survey components ✔ short survey, short/simple questions, start with demographic questions, ues dichtomous (yes-no) and multiple choice Direct observation ✔ example: counts backpacks on campus for a day stratified random sample ✔ a sample from selected subgroups of the target population in which everyone in those subgroups has an equal chance of being included in the research example: The manager of a customer service division wants to know if the customers in the past 12 months are satisfied with their purchase of CD's. There are four types of CD's. Joint Probability ✔ the probability of the intersection of two events Union of two events ✔ The union of events A and B is the event containing all sample points that are in A or B or both Marginal Probability ✔ the probability of a single event without consideration of any other event Conditional Probability ✔ the likelihood that a target behavior will occur in a given circumstance Bayes Law ✔ calculates posterior probability exhaustive ✔ including everything possible; very thorough or complete Central Limit Theorem (CLT) ✔ The name of the theorem stating that the sampling distribution of a statistic (e.g. x ) is approximately normal whenever the sample is large and random. Allows us to draw conclusions about the population based on strictly sample data. sampling distribution of the mean ✔ 1. the sampling distribution of the mean has a different mean from the original population 2. the standard deviation of the sampling distribution of the mean is referred to as the standard deviation 3. if the original population is not normally distributed, the sampling of the mean will be normal Suppose you are given 3 numbers that relate to the number of people in a sample. The three numbers are 10, 20 and 30. If the standard deviation is 10, the standard error equals ✔ 5.77 To find the standard deviation, find the mean of the data set ( 10, 20, 30) then calculate in excel. Watch video Bozeman Science Standard Error Find the sample standard deviation of 5, 10, 15 and 20. ✔ 6.45 standard deviation ✔ a computed measure of how much scores vary around the mean score Type 1 error ✔ Rejecting null hypothesis when it is true type 11 error Three concepts that a statistical inference problem contains ✔ the population, the sample, and the statistical inference Parameter ✔ a descriptive measure of a population statistic ✔ a number that describes a sample statistical inference ✔ process of making an estimate, prediction, or decision about a population based on a sample confidence level ✔ Proportion of times that an estimating procedure will be correct Confidence level + significance level ✔ = 1 simple random sampling ✔ A sampling procedure in which each member of the population has an equal probability of being included in the sample. (example - tickets in a bin each assigned a number) stratified random sampling ✔ obtained by separating the population into mutually exclusive sets of data (strata) then drawing a simple random sample from each stratum cluster sampling ✔ random sample of the groups or clusters of elements versus a simple random sample of individual objects Probability of any outcome must be between ✔ 0 and 1 Sum of all probabilities must equal: ____ ✔ 1 Three approaches to assigning probability ✔ classical approach, relative frequency approach, subjective approach Classical Approach to Probability ✔ associated with games of chance. If an experiment has N possible outcomes, this method would assign probability of 1/n to each customer. For example, the probability of a heads and tails in the flip of a coin are equal to each other. Because the sum must be 1, the probability is 1/2, or 1/6 for a dice. relative frequency approach to probability ✔ defines probability as the long run frequency in which something occurs. Example: the last 1000 students took a course, 200 got an A. The relative frequency is 20% - estimate of students that will get an A subjective approach to probability ✔ the probability is obtained on the basis of personal judgement; often the only method of assigning likelihood to an outcome; educated guess based on knowledge available union of two events ✔ Given by the outcomes that belong either to one or to both events. calculate conditional Probability ✔ P (A1/B2) Complement Probability ✔ event that occurs when A does not occur. P(A) + P(Ac) = 1 multiplication rule ✔ To determine the probability, we multiply the probability of one event by the probability of another. Addition Rule of Probability ✔ P(A or B) = P(A) + P(B) - P(AB) standard error ✔ the standard deviation of a sampling distribution Complement of an event ✔