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Subject:
Accounting, Finance, SPSS
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Multiple Choice Questions
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English (U.S.)
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Topic:
Answering questions Accounting, Finance Multiple Choice Questions
Multiple Choice Questions Instructions:
please answering the question one by one
The question is mostly related to such as covariance, variance, descriptive statistics, standard deviation, mean
please answer the question in one or two sentences.
Multiple Choice Questions Sample Content Preview:
Question Number
1 The main difference between descriptive statistics and significance test is that while descriptive statistics merely summarizes the samples and measures of the data (i.e., mean, median, mode, etc.), a significance test summarizes the evidence with the end goal of comparing the estimates of various parameters of the hypothesis (i.e., Null and Alternative) in order to prove or disprove it.
2 It is importance to determine the mean, SD, and range before running a test of dependency because the variance might change thereby changing the test statistic that should be used for the variables.
3 Knowing the level of measurement is important prior running a significance test because it is a crucial factor in determining the type of significance test to use. This is because each of these levels of measurement has different preciseness of details, which must be taken consideration even before performing any statistical test.
4 Descriptive statistics (i.e., means and standard deviations); Test Statistic (i.e., degrees of freedom); and Probability of the result (aka the p-value)
5 B (The P-value is too significant)
6 B (No)
7 A
8 The reason why we prefer to use bivariate correlations over linear regression between two interval- or ratio-level variables is because bivariate correlations does not only test the significance of the two variables’ linear relationship, but also the correlation’s strength and direction. In other words, since linear regression merely measures the correlation between data, then it is not sufficient for the level of details required in analyzing interval- or ratio-level variables.
9 The instances where we prefer the use of linear regression over a bivariate correlation are those when we deal with nominal or ordin...
1 The main difference between descriptive statistics and significance test is that while descriptive statistics merely summarizes the samples and measures of the data (i.e., mean, median, mode, etc.), a significance test summarizes the evidence with the end goal of comparing the estimates of various parameters of the hypothesis (i.e., Null and Alternative) in order to prove or disprove it.
2 It is importance to determine the mean, SD, and range before running a test of dependency because the variance might change thereby changing the test statistic that should be used for the variables.
3 Knowing the level of measurement is important prior running a significance test because it is a crucial factor in determining the type of significance test to use. This is because each of these levels of measurement has different preciseness of details, which must be taken consideration even before performing any statistical test.
4 Descriptive statistics (i.e., means and standard deviations); Test Statistic (i.e., degrees of freedom); and Probability of the result (aka the p-value)
5 B (The P-value is too significant)
6 B (No)
7 A
8 The reason why we prefer to use bivariate correlations over linear regression between two interval- or ratio-level variables is because bivariate correlations does not only test the significance of the two variables’ linear relationship, but also the correlation’s strength and direction. In other words, since linear regression merely measures the correlation between data, then it is not sufficient for the level of details required in analyzing interval- or ratio-level variables.
9 The instances where we prefer the use of linear regression over a bivariate correlation are those when we deal with nominal or ordin...
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