Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Basics of Data Analysis /24 59 Quiz | Basics of data analysis 1 / 24 What do the 'whiskers' in a boxplot typically represent? Mean and median values Maximum and minimum values excluding outliers The standard deviation of the dataset First and third quartiles 2 / 24 What scale level is required for the application of the t-test? Interval scale Ordinal scale Ratio scale Nominal scale 3 / 24 What is meant by the 'significance level' in hypothesis testing? The level at which data aligns with the predicted outcomes The probability of the hypothesis being true The probability of wrongly rejecting the null hypothesis The mean value of the data 4 / 24 What is meant by the centering property of the mean? Check 5 / 24 What best describes a factor analysis? It discovers structures within datasets. It tests the relationship between variables. It tests the effect of independent variables on dependent variables. It describes the variance between groups. 6 / 24 Which of the following scale levels allows for the most arithmetic operations? Interval scale Ratio scale Nominal scale Ordinal scale 7 / 24 What statements are correct? Analysis of variance (ANOVA) belongs to the structure-describing methods. Regression analysis is also called the "mother" of multivariate methods. Contingency analysis and discriminant analysis differ only with regard to the required scale level of the independent variables. Cluster analysis and factor analysis belong to the structure-testing methods. Cluster analysis and factor analysis aim to summarize data. 8 / 24 What is the role of dummy variables in regression analysis? To incorporate nominal data into the model To decrease the variability of the dataset To increase the complexity of the model To account for variable transformations 9 / 24 What describes an ordinal scale? A scale with a natural zero point A scale that allows only classifications A scale that allows a ranking order A scale without equal segments 10 / 24 The difference between correlation and causality is that … causality is always based on a correlation, but not vice versa. causality does not require information about the origin of the data. a correlation is always positive, whereas with causality negative values are also possible. in causality there is always a cause-effect-relationship between variables, while correlation only expresses the strength of an undirected relationship between two variables. 11 / 24 What type of analysis is most appropriate for understanding the effect of different levels of a nominal independent variable on a metric dependent variable? Correlation analysis Regression analysis Factor analysis Analysis of variance (ANOVA) 12 / 24 Which percentile is represented by the bold horizontal line in a boxplot? 50th percentile 75th percentile 100th percentile 25th percentile 13 / 24 Which of the following methods do not allow to detect outliers? Standardization of data Histograms Boxplots Calculation of the mean Calculation of the median 14 / 24 What is the primary purpose of conducting a statistical test for means? To visually represent the data distribution To confirm that data collection methods are valid To calculate the standard deviation of the dataset To identify if the difference in means is due to random variation or represents a real change 15 / 24 What statistical method divides the difference between the observed and hypothetical mean by the standard error of the mean? F-test T-statistic Z-test Chi-square test 16 / 24 What does an outlier represent in data analysis? A hypothesis that has been proven A data point that fits well within the expected range A variable that is not important to the model A data point that lies an abnormal distance from other values 17 / 24 In statistical hypothesis testing, what represents the risk of rejecting a true null hypothesis? Beta error p-value Confidence level Significance level (α) 18 / 24 In data analysis, what is meant by 'interval estimation'? None of the above Calculating the mean and standard deviation Estimating a single point value for a parameter Determining the range within which a parameter lies with a certain probability 19 / 24 What is a dummy variable? A variable without influence A variable that takes all values between 0 and 1 A variable that takes only the values 0 or 1 A continuous variable 20 / 24 What does the alternative hypothesis suggest in a statistical test? The data is insufficient for analysis. The observations are random. A change or effect contrary to the null hypothesis is expected. No change or effect is expected. 21 / 24 Which statements about statistical parameters are correct? The correlation coefficient results from the square root of the variance. The sum of the deviations from the arithmetic mean is always zero. The mean of standardized data is always 1. For normally distributed data, the following applies: mean=median=mode Only for standardized data a standard deviation can be calculated. 22 / 24 What does a two-tailed t-test in hypothesis testing involve? Only positive deviations from the mean are considered Both positive and negative deviations from the mean are considered Only negative deviations from the mean are considered Neither positive nor negative deviations from the mean are considered 23 / 24 How does multivariate analysis differ from bivariate analysis? It considers only two variables at a time. It considers more than two variables at a time. It does not involve statistical testing. It only uses categorical data. 24 / 24 What is the primary difference between exploratory and confirmatory factor analysis? Confirmatory factor analysis does not use mathematical models Exploratory factor analysis uses only metric data Confirmatory factor analysis tests a predefined structure Exploratory factor analysis cannot identify factors Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
