Statistics Concepts and Models Quiz

Pearson's r = Measures the strength of the linear relationship between two continuous variables Spearman's r = Measures the strength of the monotonic relationship between two ranked variables Parametric Correlation Coefficient = Assumes that the data follows a specific distribution, such as a normal distribution Nonparametric Correlation Coefficient = Does not make assumptions about the distribution of the data

The principle of parsimony = Simple models are preferred to complex models, especially in forecasting The shrinkage principle = Imposing restrictions on estimated parameters or forecasts often improves model performance The KISS principle = Keep it Sophistically Simple None of the above = Not applicable

Cross-section data = Data collected at a specific point in time for different entities Time-series data = Data collected over time for the same entity Panel data = Data collected over time for multiple entities None of the above = Not applicable

<p>Zero mean of the error term = The average of the error term is zero Homoscedasticity = The variance of the error term is constant across all values of the explanatory variable No serial correlation = The error terms are not correlated with each other None of the above = Not applicable</p> Signup and view all the answers

<p>An environmentalist wants to determine the relationship between the number of forest fires over the year and the number of acres burned = Regression Analysis A researcher wants to see if there is a relationship between the annual energy consumption for both natural gas and coal = Regression Analysis In a department of animal production is interested in discovering the effect of three enzymes, A,B, C for increasing daily milk of a specified type of cow = ANOVA None of the above = Not applicable</p> Signup and view all the answers

<p>Specification = The model building activity; model specification Estimation = Fitting the model to the data Verification = Testing the model Prediction = Producing forecasts and conducting forecast evaluation</p> Signup and view all the answers

<p>Mann-Whitney U Test = Non-parametric test comparing two samples ANOVA = Tests for differences among three or more means Independent T-test = Compares means of two independent groups Dependent T-test = Compares means before and after an intervention</p> Signup and view all the answers

<p>ANOVA = Population variances are approximately equal Dependent T-test = Observations are related Independent T-test = Samples are unrelated Mann-Whitney U Test = Variables measured at least ordinal scale</p> Signup and view all the answers

<p>Correlation Analysis = Measures strength of relationship between variables Post-hoc Analysis = Conducts pairwise comparisons F-test = Compares variance ratios between samples Tukey test = Used after significant ANOVA results</p> Signup and view all the answers

<p>Dependent Variable = The variable being tested and measured Independent Variable = The variable manipulated to observe effects Population = Entire group of individuals in a study Sample = A subset of the population used for analysis</p> Signup and view all the answers

<p>Independent T-test = Comparing weights of male and female infants Dependent T-test = Comparing household income before and after a program Mann-Whitney U Test = Comparing rankings of two groups ANOVA = Comparing test scores across multiple classrooms</p> Signup and view all the answers

<p>Convenience Sampling = Selecting participants based on accessibility and proximity Purposive Sampling = Intentional selection based on researcher's judgment Snowball Sampling = Referral-based sampling for hard-to-trace subjects Quota Sampling = Participants selected based on predetermined characteristics</p> Signup and view all the answers

<p>Mann-Whitney U Test = Independent or unrelated samples ANOVA = Continuous variable and normal distribution Independent T-test = Two unrelated groups Dependent T-test = Related or matched samples</p> Signup and view all the answers

<p>Type I Error = Rejecting a TRUE null hypothesis Type II Error = Accepting a FALSE null hypothesis Alpha = Probability of committing a Type I error Beta = Probability of committing a Type II error</p> Signup and view all the answers

<p>State the hypotheses = Null (Ho) and alternative (Ha) hypothesis Choose level of significance = Formulate decision rule for hypotheses Compute test statistic = Calculate value based on sample data Make a conclusion = Determine the outcome of the test</p> Signup and view all the answers

<p>Correlation = Strength and direction of a relationship Regression = Predicting the value of one variable based on another Hypothesis Testing = Determining the validity of a claim Descriptive Statistics = Summarizing and organizing data</p> Signup and view all the answers

<p>Ronald Fisher = Developed ANOVA and F-test Wilcoxon = Developed the Mann-Whitney U Test Cochran = Contributed to sampling theory Student = Introduced the t-test for small samples</p> Signup and view all the answers

<p>Continuous Variable = The variable is interval or ratio level Independence = Observations must be independent from others No Significant Outliers = Outliers should not significantly affect results Single Population = Comparison is made against a hypothesized mean</p> Signup and view all the answers

<p>Comparing One Population = Analyzing a single population against a criterion Comparing Two Populations = Comparison between two different groups Comparing Three or More Populations = An analysis involving multiple groups Hypothesis Testing = Empirical testing of population parameters</p> Signup and view all the answers

<p>Null Hypothesis (Ho) = The hypothesis assuming no effect or relationship Alternative Hypothesis (Ha) = The hypothesis proposing a change or effect Critical-value approach = Decision rule based on critical values p-value approach = Decision rule based on the probability of results</p> Signup and view all the answers

<p>Convenience Sampling = Quick and low-resource method Purposive Sampling = Focuses on specific characteristics Snowball Sampling = Participants refer other difficult-to-access subjects Quota Sampling = Ensures representation based on specific quotas</p> Signup and view all the answers

<p>Type I Error = False positive result Type II Error = False negative result Significance Level (Alpha) = Threshold for rejecting null hypothesis Power of the Test = Probability of correctly rejecting the null hypothesis</p> Signup and view all the answers

<p>Enzyme A = Increases milk production Enzyme B = Decreases milk production Enzyme C = No significant effect Enzyme D = Variable effect based on cow type</p> Signup and view all the answers

<p>Experimental Study = Scientist manipulates conditions Observational Study = Conditions are not directly controlled Cross-sectional Study = Snapshot of a population at one time Longitudinal Study = Data collected over an extended period</p> Signup and view all the answers

<p>Nominal = Categorical data without order Ordinal = Categorical data with order Interval = Numeric data with meaningful difference Ratio = Numeric data with an absolute zero</p> Signup and view all the answers

<p>Category Groups = Two or more independent categorical groups Expected Frequencies = At least one observation in each class Class Composition = Mutually exclusive categories must exist Frequency Limits = No more than 20% classes below five</p> Signup and view all the answers

<p>Manipulation = Changing variables to observe effects Control = Minimizing external factors impacting results Randomization = Ensuring each subject has an equal chance Replication = Repeating trials to ensure reliability</p> Signup and view all the answers

<p>ANOVA = Comparing means of three or more groups Chi-Square = Testing independence between two categorical variables Regression = Examining relationships between variables t-test = Comparing means of two groups</p> Signup and view all the answers

<p>Treatment = The condition applied to the subjects Response Variable = The outcome being measured Explanatory Variable = The variable being manipulated Control Group = Group not receiving treatment</p> Signup and view all the answers

<p>Independent Variable = The variable changed intentionally Dependent Variable = The variable measured for effect Hypothesis = Expected outcome of the study Sample Size = Number of subjects studied for reliability</p> Signup and view all the answers

<p>Mean = The sum of the values divided by the total number of values Median = The midpoint of the data array Mode = Value(s) which occur most frequently in a given data set Range = The highest value minus the lowest value</p> Signup and view all the answers

<p>Variance = Mean of the squared deviations of the observations from the mean Standard Deviation = The positive square root of variance; a measure of spread around the mean Range = The highest value minus the lowest value Interquartile Range = Range of the middle 50% of the observations</p> Signup and view all the answers

<p>Confidence Intervals = Estimate population parameters based on sample statistics Sampling Techniques = Methods used to select individuals from a population Correlation = Measures the strength and direction of a relationship between two variables Testing Associations = Determining the relationship between categorical variables</p> Signup and view all the answers

<p>Textual = Gives a brief and concise description in paragraph form Tabular = Large data sets organized in rows and columns Graphical = Conveys data in pictorial form to engage viewers Descriptive = Summarizes the main features of a data set</p> Signup and view all the answers

<p>Percentile = Position in hundredths that a data value holds in the distribution Decile = Position in tenths that a data value holds in the distribution Quartile = Position in fourths that a data value holds in the distribution z-score = Represents the number of standard deviations from the mean</p> Signup and view all the answers

<p>Quantitative = Mean and Standard Deviation can be applied Qualitative = Mode is applicable Ordinal = Median can be computed Interval = Can use Mean and Standard Deviation</p> Signup and view all the answers

<p>Outlier = An extremely high or low data value compared to the rest Extreme Value = A data point significantly different from the rest Influential Point = A point that significantly affects the results of statistical analysis Anomaly = A deviation from the expected pattern in the data</p> Signup and view all the answers

<p>Mean = $rac{10 + 20 + 30}{3}$ Median = Data set: 3, 5, 7, 9 (Median = 6) Mode = Data set: 1, 1, 2, 3 (Mode = 1) Range = Data set: 4, 8, 10 (Range = 6)</p> Signup and view all the answers

<p>Random Sampling = Every member has an equal chance of being selected Stratified Sampling = Population divided into subgroups before sampling Cluster Sampling = Entire groups are randomly selected, not individuals Systematic Sampling = Select every nth member from a list</p> Signup and view all the answers

<p>Replication = Applying each treatment to multiple experimental units Randomization = Ensuring fair treatment assessment without bias Blocking = Grouping units with similar responses in the absence of treatment effects Factorial Design = Investigating all possible combinations of factor levels in each trial</p> Signup and view all the answers

<p>Completely Randomized Design (CRD) = Simplest design, appropriate for homogeneous units Randomized Complete Block Design (RCBD) = Simplest design with blocking, equal units per block and treatments Latin Square Design (LS) = Used for heterogeneity patterns associated with two crossed factors Split-Plot Design (SP) = Used for two or more factors, with subplots within whole plots</p> Signup and view all the answers

<p>Balanced Incomplete Block Design (BIBD) = Used when block size is smaller than the number of treatments Factorial Design = Most efficient design for investigating multiple factors Completely Randomized Design (CRD) = Suitable for unstructured, homogeneous experimental units Randomized Complete Block Design (RCBD) = Appropriate when blocking is necessary to account for variability</p> Signup and view all the answers

<p>Analysis of Variance (ANOVA) = Parametric method for analyzing data from experiments Multivariate Analysis of Variance (MANOVA) = Parametric method for analyzing multiple dependent variables Kruskall-Wallis Test = Non-parametric method for comparing groups Mann-Whitney U Test = Non-parametric method for comparing two independent groups</p> Signup and view all the answers

<p>Python = Versatility, rich libraries for data manipulation and analysis SQL = Data extraction and transformation from databases R = Statistical computing and graphics Java = General-purpose language, less commonly used for data science</p> Signup and view all the answers

<p>Machine Learning Algorithms = Algorithms that learn from data to make predictions Supervised Learning = Learning from labeled data Unsupervised Learning = Learning from unlabeled data Reinforcement Learning = Learning from rewards and punishments</p> Signup and view all the answers

<p>SPSS = Statistical analysis, data visualization R = Statistical computing, graphics SAS = Data management, statistical analysis Stata = Econometrics, statistical analysis</p> Signup and view all the answers

<p>Mean = Average of a set of values Standard Deviation = Measure of data spread around the mean Correlation = Strength and direction of the linear relationship between two variables Regression = Predicting a dependent variable based on independent variables</p> Signup and view all the answers