Comprehensive Study Set for Business Statistics: Data Analysis for Decision Making
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Comprehensive Study Set for Business Statistics: Data Analysis for Decision Making
20 flashcards
Q1:What is the mean and how is it calculated?
A:The mean is the average of a data set, calculated by summing all values and dividing by the number of values.
Q2:What is a p-value in hypothesis testing?
A:The p-value indicates the probability of observing the test results under the null hypothesis; a lower p-value suggests stronger evidence against the null hypothesis.
Q3:What are the three measures of central tendency?
A:The three measures of central tendency are the mean, median, and mode.
Q4:Define variance. How is it different from standard deviation?
A:Variance measures the dispersion of a data set, calculated as the average of squared deviations from the mean. The standard deviation is the square root of the variance.
Q5:What is a confidence interval?
A:A confidence interval is a range of values derived from sample statistics that is likely to contain the population parameter within a specified level of confidence.
Q6:Explain the difference between qualitative and quantitative data.
A:Qualitative data represents categorical variables that can be described using words, while quantitative data represents numerical variables that can be measured.
Q7:What is regression analysis used for?
A:Regression analysis is used to identify the relationships between variables and to predict the value of a dependent variable based on independent variable(s).
Q8:What is a histogram and how is it used?
A:A histogram is a graphical representation of data distribution, showing the frequency of data points within specified intervals. It is used to visualize the shape of the data distribution.
Q9:What are outliers, and why are they important in statistics?
A:Outliers are data points significantly different from other observations and can affect the results of statistical analyses, leading to misleading conclusions.
Q10:What is the significance of the normal distribution in business statistics?
A:The normal distribution is crucial in statistics because many statistical techniques are based on the assumption of normality, facilitating probability calculations.
Q11:What is the purpose of hypothesis testing?
A:Hypothesis testing is used to evaluate assumptions (hypotheses) about a parameter in a population and determine if there is enough statistical evidence to reject or fail to reject a null hypothesis.
Q12:What is descriptive statistics?
A:Descriptive statistics summarize and describe the features of a data set, including measures of central tendency, dispersion, and data visualization techniques.
Q13:Explain what a scatter plot depicts in a given data set.
A:A scatter plot visually represents the relationship between two quantitative variables, showing how one variable is affected by another.
Q14:What does it mean if a data set is skewed?
A:Skewness indicates that the data are not symmetrically distributed; a right skew means a longer tail on the right, while a left skew indicates a longer tail on the left.
Q15:Describe the Central Limit Theorem.
A:The Central Limit Theorem states that the distribution of sample means approaches a normal distribution as the sample size increases, regardless of the population distribution.
Q16:What is the difference between Type I and Type II errors in hypothesis testing?
A:Type I error occurs when the null hypothesis is incorrectly rejected, while Type II error occurs when the null hypothesis is not rejected when it is false.
Q17:When would you use a t-test?
A:A t-test is used to determine if there is a statistically significant difference between the means of two groups, particularly when the sample size is small.
Q18:What is a box plot and what information does it convey?
A:A box plot shows the distribution of a data set based on a five-number summary (minimum, first quartile, median, third quartile, and maximum) and highlights outliers.
Q19:Define correlation and how it differs from causation.
A:Correlation measures the strength and direction of a relationship between two variables, but it does not imply that one variable causes the other.
Q20:Why is it important to use random sampling in statistics?
A:Random sampling ensures that every member of a population has an equal chance of being selected, which helps to reduce bias and improve the generalizability of results.
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