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STRAIGHTERLINE INTRODUCTION TO STATISTICS
LATEST THIS YEAR COMPLETE 50 QUESTIONS AND
CORRECT ANSWERS
QUESTION: Nominal Variable - ANSWER-categorical variables where there is no natural order among the categories
QUESTION: Ordinal variable - ANSWER-categorical variables where there is natural order among the categories
QUESTION: Interval Variable - ANSWER-a measurement or count for which it makes sense to talk about the difference between values, but it does not make sense to talk about the ratio between values; 0 does not represent the absence of quanitity
Four steps in the process of statistics - ANSWER-1. Producing Data
- Exploratory Data Analysis
- Probability
- Inference
QUESTION: Categorical variable - ANSWER-places individuals into one of several groups
Two types: nominal and ordinal
QUESTION: Quantitative Variable - ANSWER-represents a measurement or a count
Two types: Interval and ratio
QUESTION: Ratio Variable - ANSWER-quantitative variables for which it makes sense to talk about the difference between values AND the ratio between values; 0 represents the absence of quantity
QUESTION: What type of variable?:
eye color - ANSWER-nominal
QUESTION: What type of variable?:
socioeconomic status with categories low, med, high - ANSWER-Ordinal
QUESTION: What type of variable?:
Temperature - ANSWER-Interval
QUESTION: What type of variable?:
Income - ANSWER-Ratio
QUESTION: Visual display and numerical summary for a single categorical variable - ANSWER-pie chart or bar chart
and category percentages
QUESTION: Visual display and numerical summary for a single quantitative variable - ANSWER-histogram or stemplot
and descriptive statistics
QUESTION: Visual display and numerical summary for C->C - ANSWER-Two way table and conditional percentages
QUESTION: Visual display and numerical summary for C->Q - ANSWER-Side by side box plots and descriptive statistics
QUESTION: Interpreting Scatterplots:
Linear regression - ANSWER-Finding the line that best fits the pattern of the linear relationship (the line that describes how the response variable linearly depends on the explanatory variable
QUESTION: Interpreting Scatterplots:
Least Squares Regression Line - ANSWER-Has the smallest sum of squared vertical deviations of the data points from the line.
QUESTION: Interpreting Scatterplots:
Extrapolation - ANSWER-Prediction for ranges of the explanatory variable that are not in the data; is not reliable and should be avoided
QUESTION: Association (does/does not) imply causation. - ANSWER-Does not
QUESTION: Lurking Variable - ANSWER-a variable that is not among the explanatory or response variables in a study, but could substantially affect your interpretation of the relationship among those variables
QUESTION: Simpson's paradox - ANSWER-When a lurking variable causes you to rethink the direction of an association
QUESTION: Probability sampling plan - ANSWER-any sampling plan that relies on random selection (avoids bias).
QUESTION: Simple Random Sampling - ANSWER-Every member of the population has an equal probability of being selected for the sample
QUESTION: Cluster Sampling - ANSWER-Used when the population is naturally divided into groups. Take a random sample of clusters and use all individuals within those clusters as the sample.
QUESTION: Stratified sampling - ANSWER-Used when the population is naturally divided into sub- populations called stratum. Choose a simple random sample from each stratum and use these together as the sample.
QUESTION: Multistage sampling - ANSWER-a probability sampling technique involving at least two stages: a random sample of clusters followed by a random sample of people within the selected clusters
QUESTION: Observational study - ANSWER-values of the variable or variables of interest are recorded as they naturally occur; no interference
QUESTION: Sample surveys - ANSWER-a particular type of observational study in which individuals report variables' values themselves, frequently by giving their opinions.
QUESTION: Experiment - ANSWER-researchers "take control" of the values of the explanatory variable because they want to see how changes in the value of the explanatory variable affect the response variable
QUESTION: The Complement Rule - ANSWER-P(not A) = 1 - P(A)
useful for finding events of the type "at least one of..."
QUESTION: General Addition Rule - ANSWER-P(A or B) = P(A) + P(B) - P(A and B)
used to find events of the type events of the type "A or B"
QUESTION: General Multiplication Rule - ANSWER-P(A and B) = P(A) * P(B | A)
Used for events of the type "A and B"
σ^2a+bX=b^2σ^2X
QUESTION: 1. Usual
- Unusual - ANSWER-1. Within two standards deviations of the mean
- More than two standard deviations above or below the mean
QUESTION: Binomial Experiment - ANSWER-1. a fixed number of trials (notation: n trials)
- each trial must be independent of the others
- each trial has two possible outcomes, called "success" (the outcome of interest) and "failure"
- there is a constant probability (p) of success for each trial, the complement of which is the probability (1 - p) of failure
QUESTION: Binomials
The Number of outcomes with x successes out of n trials (formula) - ANSWER-[n!]/[x!*(n-x)!]
QUESTION: Mean of a binomial - ANSWER-μX=np
QUESTION: z-score for normal random variable - ANSWER-z=(x−μ)/σ
QUESTION: 1. Parameter
- Statistic - ANSWER-1. Number that describes the population
- Number that is computed from the sample
QUESTION: Standard deviation of all sample proportions - ANSWER-√,*p(1−p)+/n-.
QUESTION: Standard deviation of all sample means - ANSWER-σ/(√n)
QUESTION: 3 Types of inference in this course - ANSWER-Point estimation
Interval Estimation
Hypothesis Testing
QUESTION: In Point Estimation,
Estimate the population proportion using the ________, and the population mean using the _______. - ANSWER-Sample proportion, sample mean
QUESTION: General formula of confidence intervals - ANSWER-point estimation +- margin of error
QUESTION: Confidence intervals for the population mean - ANSWER-Xhat ± z∗⋅[σ/(√n)]
QUESTION: Various values of z for different levels of confidence - ANSWER-90%= 1.645 times the standard deviation of sample mean
· 95%= 2 (or precisely 1.96) times the standard deviation of sample mean
· 99%= 2.576 times the standard deviation of sample mean
QUESTION:
