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 does an outlier represent in data analysis? A variable that is not important to the model A data point that lies an abnormal distance from other values A hypothesis that has been proven A data point that fits well within the expected range 2 / 24 The difference between correlation and causality is that … a correlation is always positive, whereas with causality negative values are also possible. causality does not require information about the origin of the data. in causality there is always a cause-effect-relationship between variables, while correlation only expresses the strength of an undirected relationship between two variables. causality is always based on a correlation, but not vice versa. 3 / 24 What best describes a factor analysis? It tests the relationship between variables. It discovers structures within datasets. It tests the effect of independent variables on dependent variables. It describes the variance between groups. 4 / 24 How does multivariate analysis differ from bivariate analysis? It considers more than two variables at a time. It only uses categorical data. It considers only two variables at a time. It does not involve statistical testing. 5 / 24 In statistical hypothesis testing, what represents the risk of rejecting a true null hypothesis? Beta error Significance level (α) p-value Confidence level 6 / 24 What describes an ordinal scale? A scale that allows a ranking order A scale without equal segments A scale with a natural zero point A scale that allows only classifications 7 / 24 What scale level is required for the application of the t-test? Ordinal scale Ratio scale Interval scale Nominal scale 8 / 24 What do the 'whiskers' in a boxplot typically represent? Maximum and minimum values excluding outliers The standard deviation of the dataset Mean and median values First and third quartiles 9 / 24 What is meant by the centering property of the mean? Check 10 / 24 What is the primary purpose of conducting a statistical test for means? To confirm that data collection methods are valid To identify if the difference in means is due to random variation or represents a real change To calculate the standard deviation of the dataset To visually represent the data distribution 11 / 24 What is the role of dummy variables in regression analysis? To decrease the variability of the dataset To increase the complexity of the model To account for variable transformations To incorporate nominal data into the model 12 / 24 Which percentile is represented by the bold horizontal line in a boxplot? 50th percentile 75th percentile 25th percentile 100th percentile 13 / 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 14 / 24 Which of the following scale levels allows for the most arithmetic operations? Ordinal scale Nominal scale Interval scale Ratio scale 15 / 24 What statements are correct? Contingency analysis and discriminant analysis differ only with regard to the required scale level of the independent variables. Regression analysis is also called the "mother" of multivariate methods. Analysis of variance (ANOVA) belongs to the structure-describing methods. Cluster analysis and factor analysis aim to summarize data. Cluster analysis and factor analysis belong to the structure-testing methods. 16 / 24 What does the alternative hypothesis suggest in a statistical test? The data is insufficient for analysis. No change or effect is expected. The observations are random. A change or effect contrary to the null hypothesis is expected. 17 / 24 What statistical method divides the difference between the observed and hypothetical mean by the standard error of the mean? Chi-square test Z-test F-test T-statistic 18 / 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? Analysis of variance (ANOVA) Correlation analysis Regression analysis Factor analysis 19 / 24 Which of the following methods do not allow to detect outliers? Calculation of the median Boxplots Calculation of the mean Histograms Standardization of data 20 / 24 In data analysis, what is meant by 'interval estimation'? None of the above Estimating a single point value for a parameter Determining the range within which a parameter lies with a certain probability Calculating the mean and standard deviation 21 / 24 Which statements about statistical parameters are correct? The correlation coefficient results from the square root of the variance. For normally distributed data, the following applies: mean=median=mode Only for standardized data a standard deviation can be calculated. The mean of standardized data is always 1. The sum of the deviations from the arithmetic mean is always zero. 22 / 24 What is meant by the 'significance level' in hypothesis testing? The mean value of the data The probability of the hypothesis being true The level at which data aligns with the predicted outcomes The probability of wrongly rejecting the null hypothesis 23 / 24 What is the primary difference between exploratory and confirmatory factor analysis? Exploratory factor analysis uses only metric data Confirmatory factor analysis does not use mathematical models Confirmatory factor analysis tests a predefined structure Exploratory factor analysis cannot identify factors 24 / 24 What is a dummy variable? A variable that takes all values between 0 and 1 A variable that takes only the values 0 or 1 A variable without influence A continuous variable Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
