Statistical analysis of sensory data MCQs Food science December 27, 2025August 5, 2024 by u930973931_answers 50 min Score: 0 Attempted: 0/50 Subscribe 1. . Primary purpose of statistical analysis in sensory data: (A) Enhance flavor (B) Ensure food safety (C) Reduce cost (D) Analyze and interpret sensory data accurately 2. . Statistical test for comparing means of two independent samples: (A) t-test (B) Chi-square test (C) ANOVA (D) Regression analysis 3. . ANOVA stands for: (A) Analysis of Vectors (B) Analysis of Variables (C) Analysis of Variance (D) Analysis of Values 4. . Statistical method to compare means of more than two groups: (A) t-test (B) Regression analysis (C) ANOVA (D) Chi-square test 5. . A p-value indicates: (A) Probability of rejecting null hypothesis (B) Probability that null hypothesis is true (C) Probability of Type II error (D) Probability of Type I error 6. . High p-value in sensory evaluation suggests: (A) Weak evidence against null (B) Strong evidence against null (C) Null is definitely false (D) Null is definitely true 7. . Type of data typically collected in sensory studies: (A) Categorical (B) Numerical (C) All of the above (D) Ordinal 8. . Statistical technique to examine relationships between multiple variables: (A) t-test (B) Correlation analysis (C) Chi-square test (D) ANOVA 9. . Purpose of randomized complete block design (RCBD): (A) Increase sample number (B) Ensure all panelists test all samples (C) Simplify data analysis (D) Reduce variability and improve accuracy 10. . Non-parametric test in sensory evaluation: (A) t-test (B) Kruskal-Wallis test (C) ANOVA (D) Regression analysis 11. . “Degrees of freedom” refers to: (A) Number of data points (B) Number of independent values in calculation (C) Range of data set (D) Mean of data set 12. . Statistical software commonly used for sensory data: (A) Microsoft Excel (B) All of the above (C) MATLAB (D) SPSS 13. . Purpose of post-hoc test in ANOVA: (A) Compare overall means (B) Test normality (C) Identify which specific groups differ (D) Calculate mean 14. . Measure of central tendency: (A) Variance (B) Standard deviation (C) Mean (D) Range 15. . Confidence interval: (A) Standard deviation of sample (B) Probability of Type I error (C) Range within which true population parameter lies (D) Mean of sample 16. . Low standard deviation indicates: (A) High variability (B) Large sample size (C) Low variability (D) Small sample size 17. . Graphical methods to display data distribution: (A) Histogram (B) All of the above (C) Box plot (D) Scatter plot 18. . Null hypothesis in sensory evaluation: (A) Significant difference exists between samples (B) No significant difference between samples (C) Data is normally distributed (D) Sample size is adequate 19. . Statistical test for paired sample data: (A) Independent t-test (B) Chi-square test (C) ANOVA (D) Paired t-test 20. . “Replication” in sensory testing: (A) Test same sample multiple times (B) Same panelists for different tests (C) Repeat entire study (D) None of the above 21. . Measure indicating strength/direction of linear relationship: (A) Mean (B) Standard deviation (C) Correlation coefficient (D) Variance 22. . Purpose of sensory profile analysis: (A) Determine cost (B) Ensure food safety (C) Analyze consumer behavior (D) Identify and quantify sensory attributes 23. . Method to reduce dimensionality of sensory data: (A) PCA (Principal Component Analysis) (B) ANOVA (C) Regression analysis (D) t-test 24. . Outlier: (A) Most frequent value (B) Average value (C) Extremely high/low data point (D) Median value 25. . Test to compare proportion of panelists preferring a product: (A) t-test (B) ANOVA (C) Chi-square test (D) Regression analysis 26. . Purpose of sensory discrimination test: (A) Detect differences between similar products (B) Identify preferences (C) Assess quality of single product (D) Evaluate nutritional content 27. . “Panelist” in sensory evaluation: (A) Trained individual evaluating sensory attributes (B) Statistical test (C) Type of sensory test (D) Data collection method 28. . Graphical representation of sensory profile data: (A) Bar chart (B) Pie chart (C) Line graph (D) Radar plot (Spider plot) 29. . Main purpose of hedonic scale: (A) Measure intensity of attributes (B) Conduct discrimination test (C) Compare nutritional content (D) Assess overall liking/preference 30. . Measure of data dispersion: (A) Standard deviation (B) Median (C) Mean (D) Mode 31. . Statistical power: (A) Level of significance (B) Sample size required (C) Strength of test statistic (D) Probability of correctly rejecting null 32. . Test for significant difference between expected & observed frequencies: (A) Chi-square test (B) ANOVA (C) t-test (D) Regression analysis 33. . Purpose of RCBD in sensory studies: (A) Simplify analysis (B) Ensure all panelists test all samples (C) Increase sample number (D) Control variability among panelists 34. . Method to predict dependent variable from independent variables: (A) t-test (B) ANOVA (C) Regression analysis (D) Chi-square test 35. . “Latent variable”: (A) Directly measured variable (B) Used to calculate standard deviation (C) Mean of data set (D) Not directly observed, inferred from other variables 36. . Example of parametric test: (A) Wilcoxon rank-sum (B) t-test (C) Kruskal-Wallis (D) Chi-square 37. . Purpose of sensory triangle test: (A) Assess intensity (B) Determine preference (C) Compare nutritional content (D) Detect small differences between similar products 38. . Box plot displays: (A) Mean & standard deviation (B) Frequency distribution (C) Median, quartiles, potential outliers (D) Correlation between variables 39. . “Attribute” in sensory evaluation: (A) Characteristic/quality of food product (B) Statistical test (C) Type of sensory test (D) Panelist’s preference 40. . Purpose of sensory descriptive analysis: (A) Measure overall liking (B) Identify & quantify sensory attributes (C) Detect differences between similar products (D) Conduct discrimination test 41. . Non-parametric test in sensory evaluation: (A) t-test (B) ANOVA (C) Mann-Whitney U test (D) Regression analysis 42. . “Panel effect”: (A) Range of scores (B) Overall mean score (C) Influence of individual differences on results (D) Variance among attributes 43. . Measure of variation/dispersion: (A) Standard deviation (B) Mean (C) Median (D) Mode 44. . Scatter plot commonly used for: (A) Display single variable distribution (B) Compare means of multiple groups (C) Show relationship between two variables (D) Assess central tendency 45. . Test for significant difference between more than two independent groups: (A) t-test (B) ANOVA (C) Chi-square (D) Correlation analysis 46. . Multivariate analysis: (A) One variable (B) Two variables (C) Analysis of variance (D) More than two variables 47. . Example of sensory attribute: (A) Sweetness (B) All of the above (C) Texture (D) Color 48. . Purpose of sensory panel: (A) Analyze nutritional content (B) Measure physical properties (C) Conduct chemical analysis (D) Evaluate sensory attributes 49. . Method to identify patterns in large sensory datasets: (A) t-test (B) PCA (Principal Component Analysis) (C) ANOVA (D) Chi-square 50. . Sensorial fatigue: (A) Increase in sensitivity after prolonged exposure (B) Decrease in sensitivity after prolonged exposure (C) Variability among panelists (D) Range of attributes evaluated