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Karma
Class:  BUSN 231  Statistical Thinking 
Subject:  Business 
University:  Christopher Newport University 
Term:  Fall 2009 
Standard error  the amount by which the value obtained in a random sample differs from the counterpart value in the population 
Central Limit Theorem  If a population has a mean of Âµ and a standard deviation of Ï, then the distribution of sample means ( x bar ) will follow a normal distribution with a mean of Âµ and a standard deviation of Ï/ ân as long as the sample size is large enough (n â¥ 30). 
Hypothesis  a conjecture about the real world or the âstate of natureâ 
Hypothesis testing  the process of validating a belief about the value of the parameter. 
General hypothesis  hypothesis which is made up of words or sentences 
Statistical hypothesis  a hypothesis stated mathematically 
Null  not any, none, nil, suggesting a zero value 
Null hypothesis  the point of inference 
Alternate hypothesis  a statement of inequality about the value of a parameter, generally the opposite of a null hypothesis 
Test statistic  a summary measure of a sample used as evidence in the test to either support or discredit the null hypothesis 
significant difference  a difference between the hypothesized value of a parameter and the observed value of a statistic that is too great to be explained by sampling variation alone. 
Level of significance  the probability we will conclude there is a significant difference between the statistic and the parameter when the null hypothesis is true. 
decision rule  an objective statement that allows the researcher to determine whether the sample evidence supports or discredits the null hypothesis 
critical value of the statistic  the values of a statistic that separate the acceptance region from the rejection region. 
region of rejection  a set of unlikely values of the test statistic that imply rejection of the null hypothesis. 
region of acceptance  a set of values of the test statistic that we can conclude the difference between the sample mean and the hypothesized value of the mean is not a significant difference. 
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Standard error  the amount by which the value obtained in a random sample differs from the counterpart value in the population  
Central Limit Theorem  If a population has a mean of Âµ and a standard deviation of Ï, then the distribution of sample means ( x bar ) will follow a normal distribution with a mean of Âµ and a standard deviation of Ï/ ân as long as the sample size is large enough (n â¥ 30).  
Hypothesis  a conjecture about the real world or the âstate of natureâ  
Hypothesis testing  the process of validating a belief about the value of the parameter.  
General hypothesis  hypothesis which is made up of words or sentences  
Statistical hypothesis  a hypothesis stated mathematically  
Null  not any, none, nil, suggesting a zero value  
Null hypothesis  the point of inference  
Alternate hypothesis  a statement of inequality about the value of a parameter, generally the opposite of a null hypothesis  
Test statistic  a summary measure of a sample used as evidence in the test to either support or discredit the null hypothesis  
significant difference  a difference between the hypothesized value of a parameter and the observed value of a statistic that is too great to be explained by sampling variation alone.  
Level of significance  the probability we will conclude there is a significant difference between the statistic and the parameter when the null hypothesis is true.  
decision rule  an objective statement that allows the researcher to determine whether the sample evidence supports or discredits the null hypothesis  
critical value of the statistic  the values of a statistic that separate the acceptance region from the rejection region.  
region of rejection  a set of unlikely values of the test statistic that imply rejection of the null hypothesis.  
region of acceptance  a set of values of the test statistic that we can conclude the difference between the sample mean and the hypothesized value of the mean is not a significant difference. 
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