Economics: Concepts and Policies

<p>Two variables (C)</p> Signup and view all the answers

<p>Y = a + bX (A)</p> Signup and view all the answers

<p>No correlation (D)</p> Signup and view all the answers

<p>By substituting the mode with the median (C)</p> Signup and view all the answers

<p>To find the correlation in case of qualitative data (D)</p> Signup and view all the answers

<p>The value of the dependent variable is calculated based on explanatory variables (B)</p> Signup and view all the answers

<p>By dividing the explained variation by the total variation (B)</p> Signup and view all the answers

<p>The regression lines coincide perfectly (B)</p> Signup and view all the answers

<p>They are not symmetric (B)</p> Signup and view all the answers

<p>Stratification is focused on significant population characteristics, while clustering is random (D)</p> Signup and view all the answers

<p>It requires extensive time and resources (C)</p> Signup and view all the answers

<p>It helps group similar elements before selection (A)</p> Signup and view all the answers

<p>There is no linear relationship between the variables (A)</p> Signup and view all the answers

<p>$0.25$ (C)</p> Signup and view all the answers

<p>$4.56$ (B)</p> Signup and view all the answers

<p>[HH, TT, HT, TH] (A)</p> Signup and view all the answers

<p>$\frac{n(n+1)}{2}$ (C)</p> Signup and view all the answers

<p>Rejecting the null hypothesis (C)</p> Signup and view all the answers

<p>A set of values that follow a specific pattern over time (A)</p> Signup and view all the answers

<p>Each term is multiplied by a constant factor (B)</p> Signup and view all the answers

<p>$\frac{n(n+1)(2n+1)}{6}$ (B)</p> Signup and view all the answers

<p>4 (A)</p> Signup and view all the answers

<p>Comparison (D)</p> Signup and view all the answers

<p>2 (D)</p> Signup and view all the answers

<p>$\frac{a+b}{2}$ (D)</p> Signup and view all the answers

<p>The outcomes are equally likely (D)</p> Signup and view all the answers

<p>$1.645$ (C)</p> Signup and view all the answers

<p>Strong evidence against the null hypothesis (C)</p> Signup and view all the answers

<p>$npq$ (D)</p> Signup and view all the answers

<p>Mean equals variance. (C)</p> Signup and view all the answers

<p>Poisson distribution (C)</p> Signup and view all the answers

<p>Equal to 0 (D)</p> Signup and view all the answers

<p>$ ackslash sqrt{np(1-p)}$ (C)</p> Signup and view all the answers

<p>Normal distribution (C)</p> Signup and view all the answers

<p>$ ackslash sqrt{m}$ (A)</p> Signup and view all the answers

<p>1 (A)</p> Signup and view all the answers

<p>A positive value (B)</p> Signup and view all the answers

<p>The distribution has a standard deviation of 1. (C)</p> Signup and view all the answers

A statistical measure that quantifies the asymmetry of a probability distribution. It tells us how much a distribution's shape deviates from a symmetrical bell curve (normal distribution).

A statistical measure that describes the direction and strength of the linear relationship between two variables. It ranges from -1 to +1, where -1 indicates a perfect negative correlation, +1 indicates a perfect positive correlation, and 0 indicates no correlation.

A formula used to calculate the correlation coefficient (r) between two variables. It involves calculating the sum of the product of deviations from the mean of each variable.

The standard error of the correlation coefficient (r). It helps determine the statistical significance of the correlation.

A statistical equation that predicts the value of one variable (Y) based on the value of another variable (X).

The formula for the standard deviation, a measure of the spread of data points around the mean.

A formula used to calculate the coefficient of skewness, which helps to quantify the degree of asymmetry in a distribution.

The correlation between two variables when ignoring the effect of a third variable.

A statistical method used to estimate the relationship between a dependent variable and one or more independent variables. It uses a linear equation to predict the value of the dependent variable based on the values of the independent variables.

A measure of how much variation in the dependent variable is explained by the independent variable(s) in a regression model. It's represented by r-squared.

A type of sampling where the population is divided into groups or strata based on shared characteristics. Then, random samples are drawn from each stratum.

A sampling technique where the population is divided into natural clusters, and a random sample of clusters is selected. All individuals within the selected clusters are then included in the sample.

A process of collecting data from every individual in the population.

The spread of data points around the mean. It is calculated as the square root of the variance.

A statistical distribution representing the probability of a certain number of events happening in a fixed period of time or place, where these events occur independently and with a constant average rate.

The average number of events occurring within a given period of time or place. It's also the expected value of the Poisson distribution.

The square root of the mean (m) of the Poisson distribution. It measures the spread of the distribution around the mean.

The mean (m) of the Poisson distribution, calculated by multiplying the number of trials (n) by the probability of success (p).

The square root of the mean (m) of the Poisson distribution, calculated as the square root of the mean (m) itself.

A statistical distribution that models the probability of a certain number of successes in a fixed number of trials, where each trial has only two possible outcomes (success or failure), and the probability of success is constant.

The expected value of the binomial distribution, calculated by multiplying the number of trials (n) by the probability of success (p).

The square root of the product of the mean (m) and (1-p) multiplied by the number of trials (n). It measures the spread of the distribution around the mean.

The product of the mean (m) and (1-p) multiplied by the number of trials (n). It's a measure of how much the data points tend to be spread around the mean.

A special case of the binomial distribution where the number of trials is very large, and the probability of success is very small.

A type of probability where the chance of an event happening is determined by the number of favorable outcomes divided by the total number of possible outcomes.

A set of all possible outcomes in an experiment.

The probability of an event occurring is represented by a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

An event that cannot occur at the same time as another event.

An event that is independent of other events – the outcome doesn't depend on previous outcomes.

The sum of the probabilities of all possible outcomes in a sample space is always 1.

The probability of an event happening is expressed as a fraction, decimal, or percentage.

A hypothesis that the researcher aims to disprove.

A hypothesis that the researcher aims to prove.

A statistical test that helps you determine if the results of a study are statistically significant.

A sequence is an ordered list of items, where there's a specific rule or pattern determining the next item. Examples could be the population of a city over time or the amount of money saved each month.

A series is the sum of the terms in a sequence. It involves adding up all the elements in a sequence to get a total value.

An Arithmetic Progression (AP) is a sequence where the difference between consecutive terms is constant. This constant difference is called the 'common difference'.

A Geometric Progression (GP) is a sequence where each term is found by multiplying the previous term by a constant value. This constant value is called the 'common ratio'.

A series with a specific pattern where the sum of its terms can be calculated using a formula. This allows for efficient calculation of the sum of the first n terms in the series.