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# Quantitative Variables

Have you ever thought of finding the number of male and female students in your college?

Or have you ever thought about measuring the weight or height of your classmates, or recording the ages of your classmates to determine who is the youngest or oldest in your class?

All these are forms of data that can be counted and/or measured and represented in a numerical form. In statistics, these data are called quantitative variables.

In this article, we are going to study deeper into quantitative variables and how they compare to another type of variable, the qualitative variables.

## Quantitative variables meaning

Quantitative variables are variables whose values are counted.

Examples of quantitative variables are height, weight, number of goals scored in a football match, age, length, time, temperature, exam score, etc.

## Qualitative variables in statistics

Qualitative variables (also known as categorical variables) are variables that fit into categories and descriptions instead of numbers and measurements. Their values do not result from counting.

Examples of qualitative variables include hair color, eye color, religion, political affiliation, preferences, feelings, beliefs, etc.

## Types of quantitative variables

Quantitative variables are divided into two types: discrete quantitative variables and continuous quantitative variables. Details and differences between these two types of quantitative variables are explained hereafter.

## Discrete quantitative variable

Discrete quantitative variables are quantitative variables that take values that are countable and have a finite number of values. The values are often but not always integers.

The best way to tell whether a data set represents discrete quantitative variables is when the variables are countable and the number of possibilities is finite.

Continuous quantitative variables are quantitative variables whose values are not countable.

A discrete quantitative variable is a variable whose values are obtained by counting.

A continuous quantitative variable is a variable whose values are obtained by measuring.

When you count the number of goals scored in a sports game or the number of times a phone rings, this is a discrete quantitative variable.

When you measure the volume of water in a tank or the temperature of a patient, this is a continuous quantitative variable.

The table below contains examples of discrete quantitative and continuous quantitative variables,

 Discrete quantitative variables Continuous quantitative variables Number of children per household Weight Number of students in a college Speed of cars in a race Number of goals scored in a football match Height Number of correct questions answered in exams Temperature Number of people who took part in an election Time Number of students in a school Density

Distinguish the types of the following variables between discrete and continuous.

• Time taken for an athlete to complete a race,
• Depth of a river,
• Numbers of students present at school,
• Number of pets owned,

Solution

Continuous variables.

• The time taken for an athlete to complete a race, in order to see this, let us think of this situation as if we start a watch for an athlete to complete a 5000m race. From the start of the watch to the end of the race, the athlete might take 15 minutes:10 seconds:3milliseconds:5microseconds and so on depending on the precision of the stopwatch. This makes it a continuous variable.
• Depth of a river: a river may be 5m:40cm:4mm deep. Thus, the depth of a river is a continuous variable.

Discrete variables.

• Number of students present at school: this is discrete because it will always involve direct whole numbers in counting the number of students in school. We can have 1, 2, 3, 4, ...............200 students for instance present at school with a consistent interval of +1. We can never have 5.5 students or anything like that at any point. This makes it a discrete variable.
• The explanation above applies to the number of pets owned.

## Similarities between quantitative variables and qualitative variables

Primary data is the data collected by a researcher to address a problem at hand, which is classified into qualitative data and quantitative data.

Qualitative variables deal with descriptions that can be noticed but not calculated.

Quantitative variables focus on amounts/numbers that can be calculated.

✓ Both quantitative and qualitative data are used in research and analysis.

✓ Both are used in conjunction to ensure that the data gathered is free from errors.

✓Both can be obtained from the same data unit. Only their variables are different, i.e. numerical variables in case of quantitative data and categorical variables in case of qualitative data.

### Differences between quantitative and qualitative variables

 Quantitative variable Qualitative variable Can be counted and expressed in numbers and values. Cannot be counted but contains a classification of objects based on attributes, features, and characteristics. The research methodology is conclusive in nature and aims at testing a specific hypothesis to determine the relationships. The research methodology is exploratory, that is it provides insights and understanding. Has a focused approach and is objective. The research approach is subjective. Uses statistical analysis methods of analysis. The analysis is non-statistical. Ascertains the level of occurrence. Determines the depth of understanding Sample size is large and drawn from the representative sample. The sample size is usually small and is drawn from non-representative samples. Methods of data collection include experiments, surveys, and measurements. Methods of data collection include interviews, focus groups, observation, and archival materials like newspapers. Examples include height, weight, age, exam scores, etc. Examples include opinions, beliefs, eye color, description, etc.

Determine if the following variables are quantitative or qualitative variables,

• hair color
• time
• gender
• distance in kilometers
• temperature
• music genre

Solution

Qualitative variables.

• Hair color: hair colors can be grouped into various categories; whether you have blonde hair, brunette, red, or black. In a family of 5 people, 2 may have blonde hair, 2 may be brunette, 1 red, and 0 black and we can classify the people according to their hair colors. Therefore it is a categorical variable.
• Gender: this is a categorical variable because obviously, each person falls under a particular gender based on certain characteristics. A person may be a male, female, or fall under any other gender category. If there are 20 workers in a company and we want to group them according to gender, we may have 15 females and 5 males. This makes gender a qualitative variable.
• Music genre: there are different genres to classify music. Either Jazz, Rock, Hip hop, Reggae, etc.

Quantitative variables.

These are the variables that can be counted or measured.

• time in minutes: it might take a student 10 hours to finish studying this topic. Here, we are interested in the numerical value of how long it can take to finish studying a topic. This makes the time a quantitative variable.
• Temperature in degrees Celsius: the temperature of a room in degrees Celsius is a quantitative variable as it is measured and recorded in numerical as say 25, 26, or 30 degrees Celsius.
• Distance in kilometers: this is also quantitative as it requires a certain numerical value in the unit given (kilometers).

Note that the distance as a quantitative variable is given in kilometers or measurable units otherwise distance may be described as short, long, or very long which then will make the variable qualitative/categorical.

## Quantitative variables representation

Quantitative variables can generally be represented through graphs. There are many types of graphs that can be used to present distributions of quantitative variables.

✓ Stem and leaf displays/plot. A graphical type of display used to visualize quantitative data. Stem and leaf plots organize quantitative data and make it easier to determine the frequency of different types of values.

✓ Histograms. A type of graph that summarizes quantitative data that are continuous, meaning they a quantitative dataset that is measured on an interval. Histograms represent the distinctive characteristics of the data in a user-friendly and understandable manner.

✓ Frequency polygons. A line graph used for a visual representation of quantitative variables. Frequency polygons indicate shapes of distributions and are useful for comparing sets of data. In this type of data visualization, the data are plotted on a graph and a line is drawn connecting points to each other to understand the shape of the variables.

✓ Box plots. A graphical representation method for quantitative data that indicate the spread, skewness, and locality of the data through quartiles. Box plots are also known as whisker plots, and they show the distribution of numerical data through percentiles and quartiles.

✓ Bar charts. A graph in the form of rectangles of equal widths with their heights/lengths representing values of quantitative data. A bar graph/chart makes quantitative data easier to read as they convey information about the data in an understandable and comparable manner. The horizontal axis of a bar graph is called the y-axis while the vertical axis is the x-axis. Bar graphs make a comparison between data easier and more understandable.

✓ Line graphs. This is a line or curve that connects a series of quantitative data points called ‘markers’ on a graph. Similar to box plots and frequency polygons, line graphs indicate a continuous change in quantitative data and track changes over short and long periods of time.

✓ Scatter plots. Scatter plots use cartesian coordinates to show values for two variables for a set of data. Scatter plots basically show whether there is a correlation or relationship between the sets of data.

Note that some graph types such as stem and leaf displays are suitable for small to moderate amounts of data, while others such as histograms and bar graphs are suitable for large amounts of data. Graph types such as box plots are good when showing differences between distributions. Scatter plots are used to show the relationship or correlation between two variables.

## Quantitative Variables - Key takeaways

• Quantitative variables are variables whose values result from counting or measuring something.
• Quantitative variables are divided into two types: discrete and continuous variables.
• Discrete variables take values that are countable and have a finite number of values.
• Continuous variables are variables whose values are not countable and have an infinite number of possibilities.
• Examples of methods for presenting quantitative variables include Stem and leaf plots, histograms, frequency polygons, box plots, bar charts, line graphs, and scatter plots.

## Frequently Asked Questions about Quantitative Variables

Examples of quantitative variables are height, weight, number of goals scored in a football match, age, length, time, temperature, exam score, etc.

The three types of quantitative variables are discrete, continuous, and mixed quantitative variables

Quantitative variables are variables whose values are counted.

Quantitative variables are variables whose values are counted.

Quantitative variables can be counted and expressed in numbers and values while qualitative /categorical variables cannot be counted but contain a classification of objects based on attributes, features, and characteristics.

## Final Quantitative Variables Quiz

Question

What are quantitative variables?

Quantitative Variables are variables whose values result from counting or measuring something

Show question

Question

Qualitative Variables are variables that fit into categories and descriptions instead of measurements or numbers. True/False

True

Show question

Question

Quantitative variables are divided into two types, these are:

Discrete variables and continuous variables

Show question

Question

They are quantitative variables whose values are not countable and have an infinite number of possibilities.

Continuous variables

Show question

Question

A continuous variable is a variable whose value is obtained by counting. True/False

False

Show question

Question

Quantitative variables can be represented in several graph forms including………

Stem and leaf displays/plots, histograms, frequency polygons, box plots, bar charts, line graphs, and scatter plots

Show question

Question

The research approach for qualitative data is subjective and holistic. True/False

True

Show question

Question

Compared to qualitative research methodology which is exploratory, quantitative research methodology is……………

conclusive in nature and aims at testing a specific hypothesis to determine the relationships

Show question

Question

A similarity between qualitative and quantitative data is…………

Both quantitative and qualitative data could be used in research and analysis

Show question

Question

The three data analysis methods for quantitative data are …………

Cross-tabulation, Trend analysis, and Conjoint analysis

Show question

Question

The analysis method that compares data collected over a period of time with the current to see how things have changed over that period is……..

Trend analysis

Show question

Question

Examples of quantitative variables include........

Height, weight, number of goals scored in a football match, age, length, time, temperature, exam score, etc

Show question

Question

Quantitative variables are divided into _________

Discrete (categorical) and continuous variables

Show question

Question

A suitable graph for presenting large amounts of distributions of quantitative data is the _______________

Histogram

Show question

Question

Small to moderate amounts of quantitative data can be best represented using_______

Stem and leaf displays

Show question

Question

When showing differences between distributions, the best diagram to use is the____

Box plot

Show question

Question

A _________is the  suitable graph to be used to show the relationship (correlation) between two variables.

Scatter plot

Show question

Question

Both discrete and continuous variables are        ___________

Quantitative variables

Show question

Question

Both quantitative and qualitative data can be classified as ____________

Primary data

Show question

Question

Two main types of variables are ____________

Quantitative variables and Qualitative variables

Show question

Question

Quantitative variables can be categorized as

Discrete and continuous

Show question

Question

Focus Group,Observation, Interviews,Archival Materials are ________

Methods of collecting qualitative data

Show question

Question

Experiments,Surveys and Observations   Methods used for collecting data for_______

Quantitative research

Show question

Question

A method of quantitative data analysis that analyzes the relationship between multiple variables is known as____

Cross-tabulation

Show question

Question

A method of quantitative data analysis that

compares data collected over a period of time with the current to see how things have changed over that period is known as ______________

Trend analysis

Show question

Question

This type of quantitative analysis method assigns values to different characteristics and ask respondents to evaluate them.

Conjoint analysis

Show question

Question

Age,weight,height temperature etc. are examples of ___________

Continuous variables

Show question

Question

What does a box plot show us?

The spread of our data that can be interpreted with our five number summary.

Show question

Question

What are the five numbers of our five number summary?

• Minimum
• Maximum
• Median (Q2)
• Lower Quartile (Q1)
• Upper Quartile (Q3)

Show question

Question

True or False.

The order of your numbers does not matter?

False. Numbers must be ordered from least to greatest.

Show question

Question

In the following data set which numbers are the minimum and maximum:

7  12  3  15  17  19  21

7 and 21

Show question

Question

How do you find the median (Q2) of your data?

Add the numbers and divide by 2

Show question

Question

True or False.

When finding the lower quartile (Q1) and upper quartile (Q3) you do not include the median (Q2) value

True. The median (Q2) is not included in this step.

Show question

Question

Determine Q1 for the following data set:

3  5  8  10  12  12  15

10

Show question

Question

Determine the Q3 for the following data set

27  30  35  42  45

42.5

Show question

Question

IQR stands for what?

Interquartile Range

Show question

Question

How do you calculate range?

maximum - minimum

Show question

Question

If I have the following what have I just found?

Q3 = 20

Q1 = 7.5

Q3 - Q1 = 20 - 7.5 = 12.5

Range

Show question

Question

The Interquartile Range tells us what?

Where the middle 50% of our data is

Show question

Question

True or False.

The following data contains an outlier:

14  17  22  22  22  25  36

False. The upper range is 37 and the lower range is 5. All values fall within the normal range.

Show question

Question

Variation means?

How varied, or spread out, our data is.

Show question

Question

What is standard deviation?

Standard deviation is a measure of the spread of a data-set.

Show question

Question

What is a sample data set?

A sample data set is a data set that includes a representative fraction of a specified group.

Show question

Question

What is a population data set?

A population data set is a data set that includes all members of a specified group.

Show question

Question

What is the mean of a data set?

The mean of a data set is it's average value.

Show question

Question

What is the formula for the mean of a data set?

$\mu = \frac{\displaystyle \sum_{i=1}^N x_{i}}{N}$

Show question

Question

What is the formula for the standard deviation of a population data set?

$\sigma = \sqrt{\frac{\displaystyle \sum_{i=1}^N (x-\mu)^2}{N}}$

Show question

Question

What is the formula for the standard deviation of a sample data set?

$\sigma = \sqrt{\frac{\displaystyle \sum_{i=1}^N (x-\bar{x})^2}{N-1}}$

Show question

Question

What is the other name for the empirical rule?

$$68$$-$$95$$-$$99.7$$ rule

Show question

Question

What does the empirical rule state?

The empirical rule states that for most normally distributed data sets, $$68\%$$ of data points are within one standard deviation of the mean, $$95\%$$ of data points are within two standard deviations of the mean, and $$99.7 \%$$ of data points are within three standard deviations of the mean.

Show question

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text:
# GHingeLoss¶

Inheritance Diagram

class ashpy.keras.losses.GHingeLoss[source]

Bases: tensorflow.python.keras.losses.Loss

Generator Hinge Loss as Keras Metric. See Geometric GAN 1 for more details.

The Generator Hinge loss is the hinge version of the adversarial loss. The Hinge loss is defined as:

$L_{\text{hinge}} = \max(0, 1 - t y)$

where y is the Discriminator output and t is the target class (+1 or -1 in the case of binary classification). The target class of the generated images is +1.

For the case of GANs

$L_{G_{\text{hinge}}} = - \mathbb{E}_{(x \sim p_x, y \sim p_data} [ \min(0, -1+D(G(x),y)) ]$

This can be simply approximated as:

$L_{G_{\text{hinge}}} = - \mathbb{E}_{(x \sim p_x, y \sim p_data} [ D(G(x),y) ]$
1

Geometric GAN https://arxiv.org/abs/1705.02894

Methods

 Initialize the Loss. call(d_real, d_fake) Computes the hinge loss

Attributes

 reduction Return the current reduction for this type of loss.
__init__()[source]

Initialize the Loss.

Return type

None

call(d_real, d_fake)[source]

Computes the hinge loss

Return type

Tensor

property reduction

Return the current reduction for this type of loss.

Return type

ReductionV2

format: plain


text:
# Homework Help: Angular displacement and bicyclist

1. Oct 24, 2009

### Linus Pauling

1.

An exhausted bicyclist pedals somewhat erratically, so that the angular velocity of his tires follows the equation

omega(t) = 0.5t - 0.25sin(2t), t greater than/equal to zero.

where t represents time (measured in seconds).

2. omega is defined as the first derivative of theta.

3. I integrated omega(t), obtaining 0.25t^2 + (1/8)cos(2t), plugged in 2 and got my incorrect answer.

2. Oct 24, 2009

### cepheid

Staff Emeritus
Hey, can you post the actual question? Is it to find the angular displacement after 2 seconds?

3. Oct 24, 2009

### Linus Pauling

What angular displacement theta has the spot of paint undergone between time 0 and 2 seconds?

That is the question. Apparently I integrated incorrectly, but I do not see where I made a mistake.......

4. Oct 24, 2009

### cepheid

Staff Emeritus
I'm really not sure what the problem is either. Is your calculator in the right mode?

5. Oct 24, 2009

### Linus Pauling

Yes, it is in radians. So, cos(4) = -.6536

(1/8)cos(4) = -.0817

+ 1 = 0.918

??????

6. Oct 24, 2009

### Linus Pauling

BTW, it says that I did my integral wrong. In other words, the angular displacement does NOT equal:

0.25t^2 + (1/8)cos(2t)

???????????

7. Oct 24, 2009

### cepheid

Staff Emeritus
You calculated the *indefinite* integral:

$$\theta(t) = \int \omega(t) \, dt$$

$$= \int \left(\frac{1}{2}t - \frac{1}{4}\sin(2t) \right) \, dt$$

$$= \frac{1}{4}t^2 + \frac{1}{8}\cos(2t) + C$$

where C = $\theta(0)$

The question is asking you for the angular *displacement* between t = 0 and t = 2, which is given by $\theta(2) - \theta(0)$, which is given by the *definite* integral:

$$\theta(2) - \theta(0) = \int_0^2 \omega(t) \, dt$$

$$= \int_0^2 \left(\frac{1}{2}t - \frac{1}{4}\sin(2t) \right) \, dt$$

$$= \left[\frac{1}{4}t^2 + \frac{1}{8}\cos(2t)\right]_0^2$$

8. Oct 24, 2009

### Linus Pauling

Damn it, I forgot the blood 1/8 from taking cos(0).

Thank you.


text:
# System of linear equations with a unique solution

Suppose the system of linear equations $$AX=B$$ has a unique solution for some $$B$$ . Prove that rref of $$A$$ is the same as $$I_n$$. ($$A$$ is a square matrix)

My try : Because the system has a unique solution therefore it's possible to write $$x_1 = a , x_2 = b , \dots , x_n = z$$ . In the matrix form, for the coefficient matrix, we have :

$$\begin{pmatrix} 1 & 0 & 0 & \cdots & 0 \\ 0 & 1 & 0 & \cdots & 0 \\ \vdots & \vdots& \vdots & \ddots & \vdots \\ 0 & 0 & 0 & \cdots & 1 \end{pmatrix}$$ I don't know whether that's enough for proving that statement or not .

• If $\mathbf{x}_0$ is a solution to $AX=0$ and $\mathbf{x}_B$ is a solution to $AX=B$, then $\mathbf{x}_B+\mathbf{x}_0$ is a solution to $AX=B$. So if $AX=B$ has a unique solution, then $AX=0$ must also have a unique solution. Do you know anything about when homogeneous systems have unique solutions? – Arturo Magidin Jun 6 at 20:26
• @ArturoMagidin Unfortunately no . – S.H.W Jun 6 at 20:32
• Are you familiar with the concepts of rank and nullity? – paulinho Jun 6 at 20:48
• @paulinho I'm only familiar with the rank. It is the number of leading 1's in ref form. – S.H.W Jun 6 at 20:50
• Counterexample: $\begin{bmatrix}1&0\\0&1\\1&1\end{bmatrix}X=\begin{bmatrix}1\\1\\2\end{bmatrix}$. This has a unique solution, but the coefficient matrix isn’t square, so its rref can’t possibly equal the identity matrix. Seems like there are some missing conditions from the claim you’re trying to prove. – amd Jun 7 at 0:47


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# Word-mappings of level 2

Abstract : A sequence of natural numbers is said to have {\em level k}, for some natural integer $k$, if it can be computed by a deterministic pushdown automaton of level $k$ ([Fratani-Sénizergues, APAL, 2006]). We show here that the sequences of level 2 are exactly the rational formal power series over one undeterminate. More generally, we study mappings {\em from words to words} and show that the following classes coincide:\\ - the mappings which are computable by deterministic pushdown automata of level $2$\\ - the mappings which are solution of a system of catenative recurrence equations\\ - the mappings which are definable as a Lindenmayer system of type HDT0L.\\ We illustrate the usefulness of this characterization by proving three statements about formal power series, rational sets of homomorphisms and equations in words.
Keywords :
Document type :
Journal articles

https://hal.archives-ouvertes.fr/hal-00948896
Contributor : Géraud Sénizergues <>
Submitted on : Tuesday, February 18, 2014 - 5:01:48 PM
Last modification on : Tuesday, April 2, 2019 - 1:45:35 AM

### Identifiers

• HAL Id : hal-00948896, version 1

### Citation

Julien Ferté, Nathalie Marin, Géraud Sénizergues. Word-mappings of level 2. Theory of Computing Systems, Springer Verlag, 2013, 54, pp.111-148. ⟨hal-00948896⟩

Record views


text:
Education

# exponents

• 266
• 2344 Views

Exponents are shorthand for repeated multiplication of the same thing by itself. Usually, Exponent says how many times to use a number in the multiplication, In this article, we tried covering everything about the Exponents such as exponential form and product form,  positive and negative rational exponents, negative integral exponents, laws of exponents, etc. in the coming modules.

In general, we use exponents to represent large numbers in the short form so that it’s convenient to read. Base a raised to the power n is equal to multiplication of “a” n times. The Process of using Exponents is nothing but raised to the power where the exponent is called power. For better understanding, we even provided solved examples explaining step by step solution.

Example

4*4*4*4*4 can be written as 4 and is read as 4 raised to the power of 5.

In the same way, for any rational number “a”, and a is a positive integer we define an as a x a x a x a x……a(n times)

(-a)n = a if n is even

= -an if n is odd

Rational Number a is called the base whereas n is called exponent or power or index. In general, writing the product of writing a rational number by itself multiple times is called exponential notation or power notation.

Examples on Exponential Form

We can denote -3*-3*-3*-3 in the exponent form as (-3)4 and is read as -3 raised to the power of 4. in which -3 is the base.

1/2*1/2*1/2 in exponent form as (1/2) where 3 is the power and 1/2 is the base.

Examples on Product Form

We can denote (7)3 in the form of 7*7*7 and its product is 343.

### Powers with Positive Exponents

For 52 = 5*5 = 25
53 = 5*5*5 = 125
54 = 5*5*5*5 = 625

### Powers with Negative Exponents

Powers with Negative exponents is called Negative Integral Exponents.

Thus, 5-1 = 1/5

5-2 = 1/25
5-3 = 1/125

Therefore, for any non zero rational number and a positive integer, we have a-n= 1/an

a-n is the reciprocal of an.

### Solved Examples on Exponents

1. Express the following in Power Notation

(i) 1/4*1/4*1/4

= (1/4)3

(ii) (-3)*(-3)*(-3)

(-3)3

2. Express the following as Rational Numbers

(i) (2/5)3

= 2/5*2/5*2/5

= 8/125

(ii) (-2)4

= -2*-2*-2*-2

= 16/1

3. Express each of the following in the Exponential Form

(i) 625/81

We can write 625 = 5*5*5*5 = 54

81 = 3*3*3*3 = 34

Therefore, 625/81 = 54/34

(ii) -1/32

-1 = -1*-1*-1*-1*-1 = (-1)5

32= 2*2*2*2*2 = 25

Therefore, -1/32 expressed in rational number as (-1)5/25

4. Express each of the following in product form and find the value.

(i) (1/5)3
= 1/5*1/5*1/5
= 1/125

(ii) (-4)3

= -4*-4*-4

= -64

. . .


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# What effect did victory in the War of 1812 and the Treaty of Ghent have on Native Americans?A. secured

###### Question:

What effect did victory in the War of 1812 and the Treaty of Ghent have on Native Americans? A. secured their land claims east of the Mississippi River
B. open lands in the Great Lakes region to U. S. settlement
C. compelled most Native Americans to migrate north to British Canada
D. led Native Americans to form a confederation to resist U. S. expansion

### 1. Mao Zedong was a founding member of what political party? 2. Who won the Civil War in China? 3. What

1. Mao Zedong was a founding member of what political party? 2. Who won the Civil War in China? 3. What was the result of Mao’s "Great Leap Forward" program? 4. How many people died as a result of the "Cultural Revolution"?...

### Fill in the blankThe was a practice where mills that hired entire families to work there.Please give me the real awnser

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### According to the article, what are TWO benefits ofhealthy soil?SAMENA fewer pestsB nutritious foodC

According to the article, what are TWO benefits of healthy soil? SAMEN A fewer pests B nutritious food C better fertilizers D better air quality E immunity to antibiotics E improved human health...

### The following budgeted information is provided: Month 1 2 3 Sales in units 18,000 23,000 21,000 Production in units 19,000 25,000

The following budgeted information is provided: Month 1 2 3 Sales in units 18,000 23,000 21,000 Production in units 19,000 25,000 18,000 One pound of materials is required for each finished unit. The inventory of materials at the end of each month should equal 25% of the following month's production...

### The Database Administrator is an important non-technical responsible for defining and implementing consistent

The Database Administrator is an important non-technical responsible for defining and implementing consistent principles for a variety of data issues, including setting data standards and data definitions that apply across all the databases in an organization. true/false...

### 8. the amount of a person’s paycheck p varies directly with the number of hours worked t. for 22 hours of work, the paycheck

8. the amount of a person’s paycheck p varies directly with the number of hours worked t. for 22 hours of work, the paycheck is \$126.50. write an equation for the relationship between hours of work and pay....

### 2 x (c2 - 5) for c = 4 sos!!

2 x (c2 - 5) for c = 4 sos!!...

### Which of the following is a numerical expression

Which of the following is a numerical expression...

### In ΔRST, r = 9.5 cm, ∠T=123° and ∠R=40°. Find the length of s, to the nearest 10th of a centimeter.

In ΔRST, r = 9.5 cm, ∠T=123° and ∠R=40°. Find the length of s, to the nearest 10th of a centimeter....

### Read the excerpt from “George Washington.'Born in 1732 into a Virginia planter family, [George Washington] learned the morals, manners, and body of

Read the excerpt from “George Washington." Born in 1732 into a Virginia planter family, [George Washington] learned the morals, manners, and body of knowledge requisite for an 18th century Virginia gentleman. Which provides the best objective summary of this sentence? A - George Washington was ra...

### Draw an area model and then sovle useing the standard algorithm 24×21

Draw an area model and then sovle useing the standard algorithm 24×21...

### ‘Remixing technologies is how are kids speak.'' Do you agree with this statement? Why or why not?

‘Remixing technologies is how are kids speak."" Do you agree with this statement? Why or why not?...

### Find the values of m and n.

Find the values of m and n. $Find the values of m and n.$...

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