DSOM II
Extremely large or small observations for a variable are referred to as (blank)
Outliers
There is only one population, but many possible samples of a given size can be drawn from the population. Which of the following is a constant, even though its value may be unknown? Population Sampling statistic Population Parameter Sampling distribution
Population Parameter
On the basis of new information, we update the prior probability to arrive at a conditional probability called a (Blank) probability.
Posterior
Because many choices we make involve some degree of uncertainty, we are better prepared for the eventual outcome if we can use (Blank) to describe which events are likely and which are unlikely.
Probability
Subjective probability
Probability is based on an individual's personal judgment or experience.
Which of the following summarizes the two correct decisions related to Type I and Type II errors? Rejecting the null hypothesis when the null hypothesis is false Rejecting the null hypothesis when the null hypothesis is true Not rejecting the null hypothesis when the null hypothesis is true Not rejecting the null hypothesis when the null hypothesis is false
Rejecting the null hypothesis when the null hypothesis is false Not rejecting the null hypothesis when the null hypothesis is true
When determining the value tα.df, we need which two pieces of information: Alpha or degrees of freedom or sample size Degrees of freedom or alpha and sample size Sample size or degrees of freedom and Alpha sample size or alpha and degrees of freedom
Sample size or degrees of freedom and Alpha
An event is any subset of outcomes of the experiment. It is called a (Blank) event if it contains a single outcome.
Simple
We cannot describe the possible values of a (Blank) random variable X with a list x1, x2,... because the value (x1 + x2)/2, not in the list, might also be possible
continuous
A random variable summarizes the results of an experiment in terms of numerical values and can be classified as (Blank) or (Blank) depending on the range of values that it assumes.
discrete; continuous
Another standardized statistic, which uses the estimator S in place of σ, is computed as T= ̄X−μ/S/√n. Which distribution does the random variable T follow? Normal distribution Uniform distribution T distribution Poisson distribution
T distribution
Kurtosis
The blank coefficient is a summary measure that tells us whether the tails of the distribution are more or less extreme than the normal distribution.
Skewness
The blank coefficient measures the degree to which a distribution is not symmetric about its mean.
The basic principle of hypothesis testing is to first assume that the null hypothesis is 'Blank' and then determine if sample evidence contradicts this assumption.
true
An estimator is (Blank) if its expected value equals the population parameter of interest.
unbiased
Experiment
A process that leads to one of several possible outcomes.
For the 99% confidence interval, what is α/2? .005 .05 .015 .10
.005 Reason: α/2 = 0.01/2 = 0.005
Suppose we want to find the value tα,df with α = 0.010 and df = 10; that is, t0.0.10,10. Using Table 5.2, The value X suggests that P(T10 ≥ x) = 0.010; what is X? 1.282 1.372 3.078 1.812
1.372 Reason: Using Table 5.2, we look at the first column labeled df and find the row 10. We then continue along this row until we reach the column α = 0.10.
A simple probability distribution for a continuous random variable is called the: A. Normal distribution B. Continuous uniform distribution C. Discrete uniform distribution D. Bell shaped distribution
B. Continuous uniform distribution
The sampling distribution of ̄P is closely related to which distribution? Normal Uniform Poisson Binomial
Binomial
The degrees of freedom determine the extent of the broadness of the tails of the distribution; If there are fewer degrees of freedom, the tail of the distribution is more: Narrow Furry Complicated Broad
Broad
True or false: If sample evidence is inconsistent with the null hypothesis, we (Blank) the null hypothesis.
reject
Which of the following is an example of a Type II Error? Occurs when we reject the null hypothesis Can occur when the null hypothesis is true Is a correct decision Can occur when the null hypothesis is false
Can occur when the null hypothesis is false
Often it is more in-formative to provide a range of values—an interval—rather than a single point estimate for the unknown population parameter. What two terms are used for this range of values called? Hypothesis test Population range Confidence interval Interval estimate
Confidence interval Interval estimate
Sample Space
Contains all possible outcomes of the experiment.
The probability distribution of the sample mean ̄X, is also referred to as the: estimator population of X unbiased estimator Sampling distribution of ̄X
D. Sampling distribution of ̄X
We are conducting a hypothesis test using α = 0.05. H0:Do not build brick-and-mortar store. HA:Build brick-and-mortar store. We determine that the p-value is .20. What is our decision? A. Reject the null hypothesis B. Re-evaluate the alpha C. Do not reject the null hypothesis D. Collect more data
Do not reject the null hypothesis
Which of the following is true of the population proportion p? A. It is estimated on the basis of its sample counterpart, the sample proportion ̄P B. Is used for both quantitative and qualitative variables C. Is a descriptive measure for a qualitative variable D. Is used for quantitative variables of interest
It is estimated on the basis of its sample counterpart, the sample proportion ̄P Is a descriptive measure for a qualitative variable
Population
The formula for the variance differs depending on whether we have a sample or a
Recall that the population proportion p is the essential descriptive measure for a qualitative variable, and that it is estimated on the basis of its sample counterpart. What is its sample counterpart? null hypothesis p-value The sample proportion ̄P Alternative hypothesis
The sample proportion ̄P
True or false: In most applications, we require some form of the equality sign in the null hypothesis
True
True or false: The expected value of the sample proportion ̄P is equal to the population proportion; that is, E(P) =p
True
We use hypothesis testing to resolve conflicts between two competing hypotheses on a particular population parameter of interest. Which of the following corresponds to the null hypothesis? corresponding to a presumed default state of nature or status quo contradicts the default state or status quo denoted HA denoted H0
corresponding to a presumed default state of nature or status quo denoted H0
The z value associated with a probability of .5040 is
.01
For z =.11, what is the corresponding probability? A. .5438 B. None of the answers are correct C. .5398 D. .4562
.5438
Johnny feels that he has an 85% chance of getting an A in Marketing and a 45% chance of getting an A in Managerial Economics. He also believes he has a 35% chance of getting an A in both classes. What is the probability that he gets an A in at least one of these courses? A. .35 B. .85 C. .45 D. .95
0.85+0.45-0.35= D. 0.95
Association
A measure of blank quantifies the direction and strength of the linear relationship between two variables, x and y.
Probability
A numerical value that measures the likelihood that an event occurs.
An economist predicts a 70% chance that country A will perform poorly and a 35% chance that country B will perform poorly. There is also a 20% chance that both countries will perform poorly. a. What is the probability that country A performs poorly given that country B performs poorly? A. .20/.35 =.57 B. .35/.70=.50 C. .20/.7 = 028 D. None are correct
A. .20/.35 =.57
Which of the following is true of the Central Limit Theorem? A. A sample size of approximately 30 is recommended B. Works if population is larger than 30 C. Is used to approximate normal distributions D. Is useful to approximate Poisson distributions
A. A sample size of approximately 30 is recommended C. Is used to approximate normal distributions
Which of the following statements is true of the skewness coefficient? Select all that are true. A. A symmetric distribution has a skewness coefficient of zero B. A positively skewed distribution has a positive skewness coefficient C. A negatively skewed distribution has a zero skewness coefficient D. The normal distribution has a skewness coefficient of 1
A. A symmetric distribution has a skewness coefficient of zero B. A positively skewed distribution has a positive skewness coefficient
Which of the following is true of the covariance? Select all that are true! A. Covariance can be negative, positive, or zero B. The covariance is sensitive to the units of measurement C. If the covariance is negative, then x and y have a negative linear relationship. D. We can comment on the strength of the relationships using the covariance
A. Covariance can be negative, positive, or zero B. The covariance is sensitive to the units of measurement C. If the covariance is negative, then x and y have a negative linear relationship.
The chefs at a local pizza chain in Cambria, California, strive to maintain the suggested size of their 16-inch pizzas. Despite their best efforts, they are unable to make every pizza exactly 16 inches in diameter. The manager has determined that the size of the pizzas is normally distributed with a mean of 16 inches and a standard deviation of 0.8 inch. What are the expected value and the standard error of the sample mean derived from a random sample of 2 pizzas? A. E(X) =16 and se( ̄X) =0.8__√__2=0.57 B. E( ̄X) =16 and se( ̄X) =0.8__√__4=0.40 C. E(X) =12 and se( ̄X) =0.8__√__2=0.57
A. E(X) =16 and se( ̄X) =0.8__√__2=0.57
Which of the following statements is true regarding the kurtosis coefficient? Select all that are true. A. Excess kurtosis is calculated as the kurtosis coefficient minus 3 B. A platykurtic distribution is one that has shorter tails C. The kurtosis coefficient of a normal distribution is zero D. A distribution that has tails that are more extreme than the normal distribution is leptokurtic
A. Excess kurtosis is calculated as the kurtosis coefficient minus 3 B. A platykurtic distribution is one that has shorter tails D. A distribution that has tails that are more extreme than the normal distribution is leptokurtic
There are several measures of dispersion that gauge the variability of a data set. Select all of the measures below that are useful for measuring dispersion. A. Interquartile Range B. Range C. Use the mean D. Mean Absolute Deviation
A. Interquartile Range B. Range D. Mean Absolute Deviation The mean is a measure of central tendency (B)
Which of the following is true regarding the graph depicting the normal probability density function f(x)? A. Is often referred to as the normal curve B. Is often referred to as the bell curve C. Is symmetric around the mean D. Is not always symmetric around the mean
A. Is often referred to as the normal curve B. Is often referred to as the bell curve C. Is symmetric around the mean
When constructing a box plot, the first step is to use a five-number summary. What does the five-number summary contain? A. Minimum Value B. Maximum Value C. Q1, Q2, Q3, Q4 D. Q1, Q2, Q3
A. Minimum Value B. Maximum Value D. Q1, Q2, Q3
A manager believes that 20% of consumers will respond positively to the firm's social media campaign. Also, 24% of those who respond positively will become loyal customers. Find the probability that the next recipient of their social media campaign will react positively and will become a loyal customer? A. P(R ∩ L) =P(L∣R)P(R) = 0.24 × 0.20 =.048 B. P(R ∩ L) =P(R)/P(L∣R) =.20/.24 =.833 C. P(R ∩ L) =P(R ∩ L) =P(L∣ R)/P(R)= 0.24/0.20 = 1.2 D. None are correct
A. P(R ∩ L) =P(L∣R)P(R) = 0.24 × 0.20 =.048
Which of the following are common measures of shape? A. Skewness coefficient B. MAD or the Mean absolute deviation C. Kurtosis coefficient D. Range
A. Skewness coefficient C. Kurtosis coefficient
Which of the following is true of the correlation coefficient? Select all that are true! A. The correlation coefficient is unit free B. If the correlation coefficient equals 0, then x and y are not linearly related C. The value of the correlation coefficient falls between zero and 1 D. If the correlation coefficient equals −1, then x and y have a perfect negative linear relationship
A. The correlation coefficient is unit free B. If the correlation coefficient equals 0, then x and y are not linearly related D. If the correlation coefficient equals −1, then x and y have a perfect negative linear relationship
Which of the following are key properties of the discrete probability distribution? A. The probability of each value x is a value between 0 and 1, or, equivalently, 0 ≤ P(X = x) ≤ 1 B. The probabilities of success and failure remain the same from trial to trial C. The number of successes within a specified time or space interval equals any integer between zero and infinity D. The sum of the probabilities equals 1. In other words, ΣP(X = xi) = 1, where the sum extends over all values x of X
A. The probability of each value x is a value between 0 and 1, or, equivalently, 0 ≤ P(X = x) ≤ 1 D. The sum of the probabilities equals 1. In other words, ΣP(X = xi) = 1, where the sum extends over all values x of X
An experiment satisfies a Poisson process if (choose all that apply) A. The probability of success in any interval is the same for all intervals of equal size B. The number of successes counted in nonoverlapping intervals are dependent C. The probability of success in any interval is proportional to the size of the interval D. The number of successes within a specified time or space interval equals any integer between zero and infinity
A. The probability of success in any interval is the same for all intervals of equal size C. The probability of success in any interval is proportional to the size of the interval D. The number of successes within a specified time or space interval equals any integer between zero and infinity
Which of the following are the two defining properties of probability? A. The sum of the probabilities of any list of mutually exclusive and exhaustive events equals 1. B. The empirical probability of an event is the observed relative frequency with which an event occurs C. The probability of any event A is a value between 0 and 1; that is, 0 ≤ P(A) ≤ 1. D. The subjective probability is based on an individual's personal judgment or experience
A. The sum of the probabilities of any list of mutually exclusive and exhaustive events equals 1. C. The probability of any event A is a value between 0 and 1; that is, 0 ≤ P(A) ≤ 1.
Which of the following is true of the variance and standard deviation? A. The variance is an average of the squared differences between the observations and the mean B. An average of the absolute differences between the observations and the mean. C. The standard deviation is the positive square root of the variance. D. The difference between the third quartile and the first quartile
A. The variance is an average of the squared differences between the observations and the mean C. The standard deviation is the positive square root of the variance.
Which of the following is a true statement regarding outliers in data analysis? (Choose all that apply) A. There are no universally agreed upon methods for treating outliers B. Outliers may just be due to random variations C. Outliers may indicate bad data due to incorrectly recorded observations D. Outliers will not unduly affect the mean of a sample
A. There are no universally agreed upon methods for treating outliers B. Outliers may just be due to random variations C. Outliers may indicate bad data due to incorrectly recorded observations
A Bernoulli process consists of a series of n independent and identical trials of an experiment such that on each trial: (Choose all that apply!) A. There are only two possible outcomes B. The probabilities of success and failure remain the same from trial to trial C. There are more than two possible outcomes D. The probabilities of success and failure change from trial to trial
A. There are only two possible outcomes B. The probabilities of success and failure remain the same from trial to trial
Which of the following is false of measures of association? Select all that are false. A. These measures reflect the typical or central value of a variable B. These measures quantify the direction and strength of the linear relationship between two variables, x and y. C. These measures are not appropriate when the underlying relationship between the variables is nonlinear D. Measures the degree to which a distribution is not symmetric about its mean.
A. These measures reflect the typical or central value of a variable (Reason: This is the measure of central location) D. Measures the degree to which a distribution is not symmetric about its mean. (Reason: This is the skewness coefficient and is a measure of shape)
What is the probability theory rule that is a tool for breaking the computation of a probability into distinct cases? A. Total probability rule B. Bayes' Theorem C. Conditional probability D. Statistical analysis
A. Total probability rule
Scores on a management aptitude examination are normally distributed with a mean of 72 and a standard deviation of 8.We want to find the lowest score that will place a manager in the top 10% (90th percentile) of the distribution. Which of the following is true to solve this problem? A. a score of 82.24 or higher will place a manager in the top 10% of the distribution B. The 90th percentile is a numerical value x such that P(X < x) = 0.90 C. We will use the inverse transformation x + μ = zσ to solve these problems. D. z = 1.28
A. a score of 82.24 or higher will place a manager in the top 10% of the distribution B. The 90th percentile is a numerical value x such that P(X < x) = 0.90 D. z = 1.28
A standard normal table, also referred to as the z-table, provides what information that is under the z curve? A. probabilities B. Mean and variance C. standard values D. expected values
A. probabilities
Classical probabilities
Are often used in games of chance. They are based on the assumption that all outcomes of an experiment are equally likely.
Many experiments fit the conditions of a Bernoulli process. Which of the following fit the conditions of a Bernoulli process? Choose all that apply! A. A college graduate gets a job, quits school or applies to graduate school B. A college graduate applies or does not apply to graduate school C. A drug is either effective or ineffective D. A customer defaults or does not default on a loan
B. A college graduate applies or does not apply to graduate school C. A drug is either effective or ineffective D. A customer defaults or does not default on a loan (A Bernoulli process consists of two options only!)
Which of the following is false of the variance and standard deviation? A. The variance is an average of the squared differences between the observations and the mean B. An average of the absolute differences between the observations and the mean. C. The standard deviation is the positive square root of the variance. D. The difference between the third quartile and the first quartile
B. An average of the absolute differences between the observations and the mean. (Reason: This is the definition of the MAD) D. The difference between the third quartile and the first quartile (Reason: This is the interquartile range)
Which of the following are NOT common measures of shape? A. Skewness coefficient B. MAD or the Mean absolute deviation C. Kurtosis coefficient D. Range
B. MAD or the Mean absolute deviation (Reason: This is a measure of dispersion) D. Range (Reason: This is a measure of dispersion)
Which of the following is true of measures of association? Select all that are true. A. These measures reflect the typical or central value of a variable B. These measures quantify the direction and strength of the linear relationship between two variables, x and y. C. These measures are not appropriate when the underlying relationship between the variables is nonlinear D. Measures the degree to which a distribution is not symmetric about its mean.
B. These measures quantify the direction and strength of the linear relationship between two variables, x and y. C. These measures are not appropriate when the underlying relationship between the variables is nonlinear
The mean and the standard deviation of scores on an accounting exam are 74 and 8, respectively. The mean and the standard deviation of scores on a marketing exam are 78 and 10, respectively. Find the z-scores for a student who scores 90 in both classes. A. z-score in the marketing class is z=(90−78)/8=1.5 B. z-score in the accounting class is z=(90-74)/8 =2 C. z-score in the accounting class is z=(90-74)/10 =1.6 D. z-score in the marketing class is z=(90−78)/10=1.2
B. z-score in the accounting class is z=(90-74)/8 =2 D. z-score in the marketing class is z=(90−78)/10=1.2
He offers an annual bonus of $10,000 for superior performance, $6,000 for good performance, $3,000 for fair performance, and $0 for poor performance. Based on prior records, he expects an employee to perform at superior, good, fair, and poor performance levels with probabilities 0.10, 0.20, 0.50, and 0.20, respectively. Calculate the expected value of the annual bonus amount A. $4,200 B. $6,000 C. $3,700 D. $4,000
C. $3,700
He offers an annual bonus of $10,000 for superior performance, $6,000 for good performance, $3,000 for fair performance, and $0 for poor performance. Based on prior records, he has an expected value of the annual bonus of $4,000. What is the total annual amount that Brad can expect to pay in bonuses if he has 10 employees? A. You do not have enough information B. $4,000 C. $40,000 D. We need the probability of each performance level
C. $40,000 (Reason: $4000*10 = $40,000)
Johnny feels that he has a 85% chance of getting an A in Marketing and a 45% chance of getting an A in Managerial Economics. He also believes he has a 35% chance of getting an A in both classes. What is the probability that he does not get an A in either of these courses? A. .25 B. .15 C. .05 D. .10
C. 1 - (0.85+0.45−0.35)=0.05
Calculate the Mean Absolute Deviation for the following data: We have observed the age of 3 individuals in a study, where the mean age is 40. The observed ages were 31, 40, and 49. What is the MAD? A. 9 B. 6 C. -6 D. Not enough data
C. 6 Reason =abs((31-40)+(40-40) +(49-40))/3 = 6
Which of the following statements is false of the skewness coefficient? Select all that are false. A. A symmetric distribution has a skewness coefficient of zero B. A positively skewed distribution has a positive skewness coefficient C. A negatively skewed distribution has a zero skewness coefficient D. The normal distribution has a skewness coefficient of 1
C. A negatively skewed distribution has a zero skewness coefficient (Reason: A negatively skewed distribution has a negative skewness coefficient) D. The normal distribution has a skewness coefficient of 1 (Reason: The normal distribution has a skewness coefficient of zero)
For the binomial distribution, px(1 − p)n − x, represents the probability of any particular sequence with x successes and n − x failures. Use this formula to answer the following: In the Southern area of the United States, approximately 20% of adults have a college degree. We randomly ask four adults whether they have a college degree. Which of the following statements is true? A. Probability that all 4 adults have a college degree =.00032 B. p =.8 C. Probability that one adult will have a college degree = 10.24% D. n=4
C. Probability that one adult will have a college degree = 10.24% D. n=4 Reason: .24 (.8)4-4 =.0016(1) =.0016
When constructing a box plot, the first step is to use a five-number summary. What does the five-number summary NOT contain? A. Minimum Value B. Maximum Value C. Q1, Q2, Q3, Q4 D. Q1, Q2, Q3
C. Q1, Q2, Q3, Q4 (Reason: only the Q1, Q2, and Q3 are included)
Which of the following defines a probability that is based on an individual's personal judgment or experience? A. Exhaustive probability B. empirical probability C. subjective probability D. classical probability
C. Subjective Probability
Which of the following statements is false regarding the kurtosis coefficient? Select all that are false. A. Excess kurtosis is calculated as the kurtosis coefficient minus 3 B. A platykurtic distribution is one that has shorter tails C. The kurtosis coefficient of a normal distribution is zero D. A distribution that has tails that are more extreme than the normal distribution is leptokurtic
C. The kurtosis coefficient of a normal distribution is zero (Reason: The kurtosis coefficient of a normal distribution is 3.0)
Which of the following is false of the correlation coefficient? Select all that are false! A. The correlation coefficient is unit free B. If the correlation coefficient equals 0, then x and y are not linearly related C. The value of the correlation coefficient falls between zero and 1 D. If the correlation coefficient equals −1, then x and y have a perfect negative linear relationship
C. The value of the correlation coefficient falls between zero and 1 (Reason: The value of the correlation coefficient falls between −1 and 1)
The (Blank) coefficient describes both the direction and the strength of the linear relationship between x and y
Correlation
An objective numerical measure that reveals the direction of the linear relationship between two variables is called the (blank).
Covariance
For the binomial distribution, px(1 − p)n − x, represents the probability of any particular sequence with x successes and n − x failures. Use this formula to answer the following: In the Southern area of the United States, approximately 20% of adults have a college degree. We randomly ask four adults whether they have a college degree. What is the probability that none of the adults have a college degree? A. zero B. .16 C. .512 D. .4096
D. .4096 (Reason: (.2)0 (.8)4 =.4096)
Are the following examples; the return on a mutual fund, time to completion of a task, or the volume of beer sold as 16 ounces, examples of continuous or discrete random variables? A. Neither B. Discrete C. They can be discrete or continuous D. Continuous
D. Continuous
What do we refer to events which include all outcomes in the sample space? A. Inclusive B. Mutually exclusive C. Simple D. Exhaustive
D. Exhaustive
Which of the following is a false statement regarding outliers in data analysis? (Choose all that apply) A. There are no universally agreed upon methods for treating outliers B. Outliers may just be due to random variations C. Outliers may indicate bad data due to incorrectly recorded observations D. Outliers will not unduly affect the mean of a sample
D. Outliers will not unduly affect the mean of a sample (Reason: Outliers can unduly influence summary statistics such as the mean or standard deviation)
Which of the following is false of the covariance? Select all that are false! A. Covariance can be negative, positive, or zero B. The covariance is sensitive to the units of measurement C. If the covariance is negative, then x and y have a negative linear relationship. D. We can comment on the strength of the relationships using the covariance
D. We can comment on the strength of the relationships using the covariance (Reason: We CANNOT comment on the strength of the relationships, just that there is a relationship!)
Random variables can also be defined in terms of their cumulative distribution function, or, equivalently, P(X ? x). What is the correct mathematical sign (instead of the ?) in the P(X ? x) for the cumulative distribution function? A. < (less than) B. = (equal) C. >(greater than) D. ≤ (less than or equal)
D. ≤ (less than or equal)
Which term describes a compilation of facts, figures or other contents, both numerical and nonnumerical?
Data
Intersection of two events
Denoted A ∩ B, is the event consisting of all outcomes in A and B
Union of two events
Denoted A ∪ B, is the event consisting of all outcomes in A or B.
Complement of event A
Denoted Ac, is the event consisting of all outcomes in the sample space S that are not in A
A (Blank) random variable assumes a countable number of distinct values such as x1, x2, x3, and so on
Discrete
What type of variable assumes a countable number of distinct values such as x1, x2, x3, and so on?
Discrete
In many instances, we calculate probabilities by referencing data based on the observed outcomes of an experiment. Which probability category is defined as the observed relative frequency with which an event occurs? A. Classical probabilities B. Subjective probability C. Empirical probability D. None are correct
Empirical probability
When a statistic is used to estimate a parameter, it is referred to as an
Estimator
True or false: A discrete random variable is characterized by uncountable values, whereas a continuous random variable assumes a countable number of distinct values.
False
True or false: The sum of the probabilities of any list of mutually exclusive and exhaustive events do not always equal 1.
False
True or false: The joint probability of events A and B is derived as P(A ∩ B) = P(A ∣ B)P(A).
False; The joint probability of events A and B is derived as P(A ∩ B) = P(A ∣ B)P(B).
What are some commonly used terms for the normal distribution? A. Gaussian distribution B. Discrete distribution C. Poisson distribution D. Bell-shaped distribution
Gaussian distribution Bell-shaped distribution
Two events are (Blank) if the occurrence of one event does not affect the probability of the occurrence of the other event.
Independent
Information
Information is DATA that has been organized, analyzed and processed in a meaningful and purposeful way
Which of the following is true regarding the graph depicting the normal probability density function f(x)? A. Is not always symmetric around the mean B. Is often referred to as the normal curve C. Is often referred to as the bell curve D. Is symmetric around the mean
Is often referred to as the normal curve Is often referred to as the bell curve Is symmetric around the mean
What is the term used in a confidence interval that accounts for the standard error of the estimator and the desired confidence level of the interval? Estimate error Point estimate Sample proportion Margin of error
Margin of error
What is the most widely used continuous probability distribution?
Normal Distribution
For making statistical inferences, it is essential that the sampling distribution of ̄X is
Normally distributed
Because almost all observations fall within three standard deviations of the mean, it is common to treat an observation as an (Blank) if its z-score is more than 3 or less than −3
Outlier
Scores on a management aptitude exam are normally distributed with a mean of 72 and a standard deviation of 8. If we are trying to find the probability that a randomly selected manager will score above 75, what is the corresponding Z value? P(Z >-.375) P(Z>-1.5) P(Z >.375) P(Z>1.5)
P(Z >.375) ( Reason: P(Z>75−72875−728=P(Z >.375) )
The original probability is an unconditional probability called a (Blank) probability, in the sense that it reflects only what we know now before the arrival of any new information.
Prior
We generally test for the independence of two events by comparing the conditional probability of one event, for instance P(A∣B), to the probability, P(A). If these two probabilities are the (Blank), we say that the two events, A and B, are independent; if the probabilities differ, the two events are (Blank)
Same; Dependent
Conditional probability
The total probability rule is a useful tool for breaking the computation of a probability into distinct cases
Statistical analysis
The total probability rule is a useful tool for breaking the computation of a probability into distinct cases
True or false: The probability that A occurs given that B has occurred is derived as P(A∣B)=P(A∩B)/P(B)
True
True or false: z-score measures the relative location of an observation and indicates whether it is an outlier.
True
knowledge
We use a blend of DATA, contextual information, experience and intuition to derive knowledge from data and information
The standard normal distribution is a special case of the normal distribution with a mean equal to
Zero
We have used the total probability rule as well as Bayes' theorem based on two mutually exclusive and exhaustive events, namely, B and Bc. We can easily extend the analysis to include (Blank) mutually exclusive and exhaustive events
n
For a Poisson process, we define the number of (Blank) achieved in a specified time or space interval as a Poisson random variable.
successes
Bayes' Theorem
uses this rule to update the probability of an event that has been affected by a new piece of evidence