Psych Stats Finals PDF

1. STATISTICS is the branch of mathematics that deals with the collection, organization, presentation, analysis, and interpretation of numerical data for the purpose of assisting in making a more effective decision. 2. Data Analysis refers to the manner of describing the properties, characte...

1. STATISTICS is the branch of mathematics that deals with the collection, organization, presentation, analysis, and interpretation of numerical data for the purpose of assisting in making a more effective decision. 2. Data Analysis refers to the manner of describing the properties, characteristics, or behavior of the data. 3. The statistical activity that refers to the exposition and arrangement of data in an appropriate manner is Data Presentation. 4. The statistical activity that involves the process of gathering numerical information is Data Collection. This includes methods such as interviews, questionnaires, experiments, observations, and documentary analysis to gather relevant data for analysis. 5. Interpretation of data involve the explanation of the meaning of the statistical finding for the formation of valid conclusions and inferences 6. Temperature readings would be classified as interval data. 7. Ranking is an example of ordinal data. 8. A jersey number is considered nominal data. 9. The manner of identifying what the characteristics of descriptive statistics is by looking at the objective which is simply describing and summarizing the important values. 10. Which among the statements describes inferential statistics? It demands a higher order of critical judgment. 11. Thoughts and knowledge come from within us, and the understanding of self allows one to live a virtuous life is believed by: socrates 12. Aristotle stressed on the importance of experience rather than reasons, that man’s reasoning is a form of making generalizations from experiences and observations made 13. Sir Francis Galton investigated the statistical technique of correlation and develop the index, to be named the coefficient of correlation 14. Descriptive Statistics is a field of statistics that includes the methods of collecting, classifying, graphing, and averaging the data 15. Descriptive Statistics simply describe and summarize the important features, properties, or characteristics of the data on hand without attempting to give inference 16. Getting the census of the iq level of the psychology student in the university is of little value if it is just a mass of numerical data It can be meaningful if it can be organized into a sort of table called FREQUENCY DISTRIBUTION or some kind of bar graph or pie graph that will give the IQ level and description when grouped according to Year level and gender. This is an example of what field of statistics? Descriptive Statistics 17. To predict academic performance or to estimate the "true" average score of a population based on data gathered from the sample is an example of what field of stats? Inferential statistics. 18. Though tests tell us that there is a significant difference in the data but as to where the difference lies, it must be tested further by another test. What do you call this test? Scheffé's test. 19. In a parametric test, the measure of central tendency valued is: Mean 20. In non-parametric tests, the measure of central tendency is typically the median. 21. Choosing the correct analytical approach is determined by the following consideration, EXCEPT: The convenience of using the analytical approach. The "convenience" of using a particular analytical approach is not a valid consideration in determining the appropriate method; the decision should be based on the data's characteristics and the research question. 22. The age of Grade 7 students does not describe a multivariable distribution, as it only involves one variable: age. A multivariable distribution involves more than one variable. 23. The type of scale that has no numerical value is the nominal scale. 24. The type of scale typically used in questions that call for rating quality is the ordinal scale 25. The type of scale that does not have a true zero point is the interval scale. 26. The scale that represents the highest and most precise level of measurement is the ratio scale. 27. The scale that is also known as a categorical scale is the nominal scale. 28. The type of scale that puts subjects in order from highest to lowest or from most to least is the ordinal scale. 29. The following statements describe a null hypothesis, except: It is generally the hypothesis that the researcher is trying to prove and states that independent variable has an effect and there will be a difference between the two groups. This describes the alternative hypothesis, not the null hypothesis. 30. A non-directional hypothesis predicts that there will be a difference between groups but does not specify the direction of the difference (e.g., one group being greater or less than the other). It simply states that a difference exists. 31. A directional hypothesis uses comparison terms such as "greater," "less," "better," or "worse," indicating the expected direction of the difference between groups or variables. For example, "Group A will perform better than Group B" is a directional hypothesis. 32. An inductive hypothesis is formed from generalizations based on observations or patterns. 33. the following statements exemplify an alternative hypothesis. Which one IS NOT true about alternative hypothesis? This is a statement of equality or no difference between the groups under study, or hypothesis of no effect. This statement describes the null hypothesis, not the alternative hypothesis. 34. The Kruskal-Wallis test is a rank-based, non-parametric test used to determine if there are statistically significant differences between two or more independent groups on a continuous or ordinal dependent variable. It is often used when the  assumptions for ANOVA (a parametric test) are not met, such as when the data is not normally distributed. 35. The Friedman test is a non-parametric test used when there are three or more related conditions (or groups), and you want to determine if there are statistically significant differences between them. It is typically used when the scores are related (e.g., repeated measures) but calculating the difference between two conditions is not feasible 36. The Wilcoxon signed-rank test is a non-parametric test used as an alternative to the paired sample t-test when the population cannot be assumed to be normally distributed. 37. The Mann-Whitney U test is a non parametric test where different participants do each condition and because participant do only one condition, it is not possible to compare the scores on both condition for each participant 38. The McNemar's test is a chi-square test for situations when samples are matched, that is, they are not independent. this is also a before and after design which is tested to find out whether there is a significant change between before and after situations. 39. The interval scale is a scale which has all the characteristics of a nominal scale and an ordinal scale but is based upon predetermined equal intervals. 40. The ratio scale is a type of scale which has a meaningful true zero point or a point where none of the quality being measured exists 41. The following statements describe a population, EXCEPT: A set of individuals, objects, observations, reactions that truly represents the unique qualities or characteristics of the population.This statement describes a sample, not a population 42. If the researcher tested all 6,000 students (the entire population) and computed measures of central tendency, variability, or correlation coefficients, the values obtained would be parameters. 43. Statistics are the measures that the researcher would have computed about the sample. 44. The following statements are true about probability sampling. EXCEPT: When the researcher is not after generalizing the results of the study to the population or universe.This statement is not true about probability sampling. 45. symmetrical distribution is described by the following, except: there is a tendency that the mean, median and mode are in different positions. This statement is not true about a symmetrical distribution. 46. The mean is the sum of all the values of the variables divided by the number of observations. 47. The mean is a measure of central tendency calculated by adding all the scores in a selection (or population) and then dividing the sum by the total number of observations or individuals in the population 48. The most common measure of central tendency is the mean. 49. The midpoint of a distribution is typically referred to as the median. 50. The middle score in a distribution is the median. 51. We use the median as a measure of central tendency if the resulting mean produces a skewed or misleading result due to outliers or extreme values. 52. Aristotle stressed on the importance of experience rather than reasons, that man’s reasoning is a form of making generalizations from experiences and observations made 53. A continuous variable can take any value within a given range and can be measured with fine precision. Beauty can be considered a continuous variable when measured on a scale (such as a rating scale or beauty index), as it can take many different values and is not restricted to distinct categories. 54. Inferential statistics is used to predict academic performance or to estimate the "true" average score of a population based on data gathered from the sample is an example of what field of statistics 55. A frequency distribution is an organized tabulation of the number of individuals or observations located in different categories or levels of measurement. 56. Which of the tolowing DOES NOT describe a statistical package for social sciences (SPSS)? Answer is: It is not really intended for statistical testing, but it is more flexible depending on how it will be used.This statement does not accurately describe the Statistical Package for the Social Sciences (SPSS). 57. Which of the following BEST DESCRIBES an MS Excel application in terms of statistical function? It is possible to run statistical analysis. 58. It is one form of representation that presents data in the form of words. sentences and paragraphs. Verbal representation 59. Tabular representation involves organizing information in a grid-like structure using rows and columns. 60. Graphical representation involves using intuitive charts (such as bar charts, line graphs, pie charts, etc.) to visualize data. 61. A frequency distribution is an organized tabulation of the number of individuals or observations located in different categories or levels of measurement. 62. Inferential statistics involves making decisions or inferences about a population based on the information gathered from the samples. 63. The following are all examples of an application of descriptive statistics, EXCEPT: The experiment was made to test the relationship of the IQ and Self-efficacy.This is an example of inferential statistics, as it involves testing a relationship (likely through hypothesis testing or correlation), which goes beyond just summarizing data. 64. The statements below characterize variables except ONE which describes a measurement Which of the statements describes measurement? The process of determining the value or label of a particular variable for a particular individual or object on which the variable is measured. This statement describes  measurement, as it refers to the process of assigning a value or label to a variable for a specific object or individual. 65. The researcher would like to determine the predictive validity of entrance requirements for freshmen students. Which of the following variables is a dependent variable? Performance in first year college. in this scenario, the researcher is interested in determining how well the entrance requirements (e.g., National Achievement Test Result, Entrance Examination Result) predict the performance in first-year college. Since the performance in college is the outcome being predicted or influenced by the entrance requirements, it is the dependent variable. 66. The independent variable is the variable that the researcher controls or manipulates in an experiment to observe its effect on the dependent variable. 67. Standard Deviation is a measure of variation which is computed by getting the square root of the variance 68. The most important measure of variability is typically the standard deviation. 69. The standard deviation allows for precise interpretation of scores within a distribution by indicating how much individual scores deviate from the mean. 70. Hypotheses are tentative guesses or assumptions made to explain phenomena, guide research, or devise theories. 71. This is NOT a characteristics of a hypothesis: “Hypothesis should not be limited in scope.” A good hypothesis should actually be limited in scope, as it is meant to address a specific research question or problem. 72. Inductive and Deductive hypothesis is based on their derivation 73. This is not true about a z-test: used when the samples are drawn from different populations. 74. The Spearman Rank Order Correlation is used when both variables are measured on an ordinal scale. 75. NOT TRUE about simple linear regression analysis: Used without computing for the correlation of variables.This statement is NOT TRUE because in simple linear regression analysis, the relationship between the independent variable (x) and the dependent variable (y) is often examined first using correlation. 76. Analysis of Variance (ANOVA).a statistical tool seems like a t-test except that t-test is limited to situations in which there are only two treatments to compare. This is a parametric test which can be used to compare two or more treatments. 77. Non parametric tests are used in the following conditions, except when: The mean, median, and mode have the same values. 78. Characteristics that BEST describes a Type II error in hypothesis testing? This occurs when it was concluded that the two drugs produced the same effect, when in fact they produced different ones. 79. This DOES NOT describe a level of significance: It is the probability of a type II error. 80. A one sided test is described by the following statements, EXCEPT: The critical region is the set of values less than the first critical value of the test and the  set of values greater than a second critical value of the test. This is false because a one-sided test only has one critical value, and the critical region is in one tail (either less than or greater than the critical value). A two-sided test would involve two critical values (one on each tail of the distribution). 81. A two-sided test is BEST described as: The critical region is the set of values less than the first critical value of the test and the set of values greater than a second critical value of the test. This correctly describes a two-sided test, where the critical region is in both tails of the distribution (values smaller than the first critical value and larger than the second critical value). 82. This statement defines a p-value: It does not give the level of significance as this is something that is done before the experiment or testing the hypothesis is done.