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Correlation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. For example, the number of crimes (per capita) is related to the number of police officers in a given area. When more police officers are on patrol, crime tends to be lower and, when fewer police officers are present, the crime rate usually increases. Consequently, the number of police officers and the crime rate have a strong negative correlation. A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. Correlation as a statistic cannot explain why or how the relationship between two variables, x and y, exists; only that it does exist. Causationgoes a step further than correlation by indicating that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. That is, a change in the value of the x variable will cause a change in the value of the y variable.
patient waiting times in the tardis orthopedic clinic have a mean of 50 minutes with a standard deviation of 25
Sample data are reported for 50 employees of small companies, 75 employees of medium companies, and 100 employees of large companies.
Your research is to determine if the value of Qatar's import of food from other GCC countries (KSA, UAE, Bahrain, Kuwait, and Oman) depends on Qatar's GDP, the GDP of the trading partners.
Use this information to compute a 95% confidence interval for average number of credit cards carried by students.
The mean tar content of a simple random sample of 25 unfiltered king size cigarettes is 21.1 mg, with a standard deviation of 3.2 mg.
Create a scenario for applying the Goodness of Fit application of Chi-square. State the hypotheses, the level of significance, the result and its meaning.
your price per unit (P), and the number of units (U) sold, you can use a mathematical equation to determine your net income (NI). In this case the formula is: NI = [U * (P-VCu)] - FC.
Suppose that 1% of all the students seeking treatment at the school infirmary have mono. Of the students who do have mono, 90% complain of a sore throat. Of the students who do not have mono, 30% also have sore throats.
Suggests a survey of area restaurants to see if the situation is pervasive. What do you think of this research suggestion? How could you improve on your boss's formulation of the research question?
Which of the following does not explain a possible relationship between variables when the null hypothesis is rejected?
Perhaps you have a millionaire, someone making $30,000 and a lot of people spread out all over (and evenly) in between. How would this need to change for median to be a better measure?
The counts in the five groups are 113, 95, 108, 99, and 85, respectively. The probabilities for these five intervals are all the same. What is this probability?
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