Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Basics of Data Analysis /24 60 Quiz | Basics of data analysis 1 / 24 What is the role of dummy variables in regression analysis? To decrease the variability of the dataset To incorporate nominal data into the model To increase the complexity of the model To account for variable transformations 2 / 24 Which percentile is represented by the bold horizontal line in a boxplot? 25th percentile 50th percentile 75th percentile 100th percentile 3 / 24 What is meant by the 'significance level' in hypothesis testing? The probability of wrongly rejecting the null hypothesis The probability of the hypothesis being true The mean value of the data The level at which data aligns with the predicted outcomes 4 / 24 What describes an ordinal scale? A scale that allows a ranking order A scale that allows only classifications A scale without equal segments A scale with a natural zero point 5 / 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? Regression analysis Factor analysis Correlation analysis Analysis of variance (ANOVA) 6 / 24 How does multivariate analysis differ from bivariate analysis? It only uses categorical data. It considers more than two variables at a time. It does not involve statistical testing. It considers only two variables at a time. 7 / 24 In data analysis, what is meant by 'interval estimation'? Estimating a single point value for a parameter None of the above Determining the range within which a parameter lies with a certain probability Calculating the mean and standard deviation 8 / 24 What statistical method divides the difference between the observed and hypothetical mean by the standard error of the mean? F-test Chi-square test T-statistic Z-test 9 / 24 What is a dummy variable? A variable that takes only the values 0 or 1 A variable without influence A variable that takes all values between 0 and 1 A continuous variable 10 / 24 What does a two-tailed t-test in hypothesis testing involve? 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 Only positive deviations from the mean are considered 11 / 24 What scale level is required for the application of the t-test? Interval scale Nominal scale Ordinal scale Ratio scale 12 / 24 What do the 'whiskers' in a boxplot typically represent? Maximum and minimum values excluding outliers First and third quartiles The standard deviation of the dataset Mean and median values 13 / 24 Which of the following scale levels allows for the most arithmetic operations? Ratio scale Ordinal scale Interval scale Nominal scale 14 / 24 What does an outlier represent in data analysis? A data point that fits well within the expected range A hypothesis that has been proven A data point that lies an abnormal distance from other values A variable that is not important to the model 15 / 24 What is the primary difference between exploratory and confirmatory factor analysis? Exploratory factor analysis cannot identify factors Confirmatory factor analysis does not use mathematical models Confirmatory factor analysis tests a predefined structure Exploratory factor analysis uses only metric data 16 / 24 What statements are correct? Regression analysis is also called the "mother" of multivariate methods. Cluster analysis and factor analysis aim to summarize data. Contingency analysis and discriminant analysis differ only with regard to the required scale level of the independent variables. Analysis of variance (ANOVA) belongs to the structure-describing methods. Cluster analysis and factor analysis belong to the structure-testing methods. 17 / 24 The difference between correlation and causality is that … causality does not require information about the origin of the data. causality is always based on a correlation, but not vice versa. 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. 18 / 24 What is the primary purpose of conducting a statistical test for means? 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 confirm that data collection methods are valid To visually represent the data distribution 19 / 24 What is meant by the centering property of the mean? Check 20 / 24 What best describes a factor analysis? It describes the variance between groups. It tests the relationship between variables. It discovers structures within datasets. It tests the effect of independent variables on dependent variables. 21 / 24 Which statements about statistical parameters are correct? 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. The correlation coefficient results from the square root of the variance. For normally distributed data, the following applies: mean=median=mode 22 / 24 Which of the following methods do not allow to detect outliers? Calculation of the mean Histograms Boxplots Standardization of data Calculation of the median 23 / 24 What does the alternative hypothesis suggest in a statistical test? The data is insufficient for analysis. The observations are random. No change or effect is expected. A change or effect contrary to the null hypothesis is expected. 24 / 24 In statistical hypothesis testing, what represents the risk of rejecting a true null hypothesis? Significance level (α) Confidence level p-value Beta error Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
