# Symbols and their meanings

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This module defines symbols used throughout the Collaborative Statistics textbook.
Symbols and their meanings
Chapter (1st used) Symbol Spoken Meaning
Sampling and Data $\sqrt{}$ The square root of same
Sampling and Data $\pi$ Pi 3.14159… (a specific number)
Descriptive Statistics $\mathrm{Q1}$ Quartile one the first quartile
Descriptive Statistics $\mathrm{Q2}$ Quartile two the second quartile
Descriptive Statistics $\mathrm{Q3}$ Quartile three the third quartile
Descriptive Statistics $\mathrm{IQR}$ inter-quartile range Q3-Q1=IQR
Descriptive Statistics $\overline{x}$ x-bar sample mean
Descriptive Statistics $\mu$ mu population mean
Descriptive Statistics $s$ ${s}_{x}$ $\mathrm{sx}$ s sample standard deviation
Descriptive Statistics ${s}^{2}$ ${s}_{x}^{2}$ s-squared sample variance
Descriptive Statistics $\sigma$ ${\sigma }_{x}$ $\mathrm{\sigma x}$ sigma population standard deviation
Descriptive Statistics ${\sigma }^{2}$ ${\sigma }_{x}^{2}$ sigma-squared population variance
Descriptive Statistics $\Sigma$ capital sigma sum
Probability Topics $\left\{\right\}$ brackets set notation
Probability Topics $S$ S sample space
Probability Topics $A$ Event A event A
Probability Topics $P\left(A\right)$ probability of A probability of A occurring
Probability Topics $P\left(A\mid B\right)$ probability of A given B prob. of A occurring given B has occurred
Probability Topics $P\left(A\mathrm{or}B\right)$ prob. of A or B prob. of A or B or both occurring
Probability Topics $P\left(A\mathrm{and}B\right)$ prob. of A and B prob. of both A and B occurring (same time)
Probability Topics $\mathrm{A\text{'}}$ A-prime, complement of A complement of A, not A
Probability Topics $P\left(\mathrm{A\text{'}}\right)$ prob. of complement of A same
Probability Topics ${G}_{1}$ green on first pick same
Probability Topics $P\left({G}_{1}\right)$ prob. of green on first pick same
Discrete Random Variables $\mathrm{PDF}$ prob. distribution function same
Discrete Random Variables $X$ X the random variable X
Discrete Random Variables $\mathrm{X~}$ the distribution of X same
Discrete Random Variables $B$ binomial distribution same
Discrete Random Variables $G$ geometric distribution same
Discrete Random Variables $H$ hypergeometric dist. same
Discrete Random Variables $P$ Poisson dist. same
Discrete Random Variables $\lambda$ Lambda average of Poisson distribution
Discrete Random Variables $\ge$ greater than or equal to same
Discrete Random Variables $\le$ less than or equal to same
Discrete Random Variables $=$ equal to same
Discrete Random Variables $\ne$ not equal to same
Continuous Random Variables $f\left(x\right)$ f of x function of x
Continuous Random Variables $\mathrm{pdf}$ prob. density function same
Continuous Random Variables $U$ uniform distribution same
Continuous Random Variables $\mathrm{Exp}$ exponential distribution same
Continuous Random Variables $k$ k critical value
Continuous Random Variables $f\left(x\right)=$ f of x equals same
Continuous Random Variables $m$ m decay rate (for exp. dist.)
The Normal Distribution $N$ normal distribution same
The Normal Distribution $z$ z-score same
The Normal Distribution $Z$ standard normal dist. same
The Central Limit Theorem $\text{CLT}$ Central Limit Theorem same
The Central Limit Theorem $\overline{X}$ X-bar the random variable X-bar
The Central Limit Theorem ${\mu }_{x}$ mean of X the average of X
The Central Limit Theorem ${\mu }_{\overline{x}}$ mean of X-bar the average of X-bar
The Central Limit Theorem ${\sigma }_{x}$ standard deviation of X same
The Central Limit Theorem ${\sigma }_{\overline{x}}$ standard deviation of X-bar same
The Central Limit Theorem $\Sigma X$ sum of X same
The Central Limit Theorem $\Sigma x$ sum of x same
Confidence Intervals $\text{CL}$ confidence level same
Confidence Intervals $\text{CI}$ confidence interval same
Confidence Intervals $\text{EBM}$ error bound for a mean same
Confidence Intervals $\text{EBP}$ error bound for a proportion same
Confidence Intervals $t$ student-t distribution same
Confidence Intervals $\text{df}$ degrees of freedom same
Confidence Intervals ${t}_{\frac{\alpha }{2}}$ student-t with a/2 area in right tail same
Confidence Intervals $\mathrm{p\text{'}}$ $\stackrel{^}{p}$ p-prime; p-hat sample proportion of success
Confidence Intervals $\mathrm{q\text{'}}$ $\stackrel{^}{q}$ q-prime; q-hat sample proportion of failure
Hypothesis Testing ${H}_{0}$ H-naught, H-sub 0 null hypothesis
Hypothesis Testing ${H}_{a}$ H-a, H-sub a alternate hypothesis
Hypothesis Testing ${H}_{1}$ H-1, H-sub 1 alternate hypothesis
Hypothesis Testing $\alpha$ alpha probability of Type I error
Hypothesis Testing $\beta$ beta probability of Type II error
Hypothesis Testing $\overline{\mathrm{X1}}-\overline{\mathrm{X2}}$ X1-bar minus X2-bar difference in sample means
${\mu }_{1}-{\mu }_{2}$ mu-1 minus mu-2 difference in population means
$P{\text{'}}_{1}-P{\text{'}}_{2}$ P1-prime minus P2-prime difference in sample proportions
${p}_{1}-{p}_{2}$ p1 minus p2 difference in population proportions
Chi-Square Distribution ${Χ}^{2}$ Ky-square Chi-square
$O$ Observed Observed frequency
$E$ Expected Expected frequency
Linear Regression and Correlation $y=a+\mathrm{bx}$ y equals a plus b-x equation of a line
$\stackrel{^}{y}$ y-hat estimated value of y
$r$ correlation coefficient same
$\epsilon$ error same
$\mathrm{SSE}$ Sum of Squared Errors same
$1.9s$ 1.9 times s cut-off value for outliers
F-Distribution and ANOVA $F$ F-ratio F ratio

can someone help me with some logarithmic and exponential equations.
20/(×-6^2)
Salomon
okay, so you have 6 raised to the power of 2. what is that part of your answer
I don't understand what the A with approx sign and the boxed x mean
it think it's written 20/(X-6)^2 so it's 20 divided by X-6 squared
Salomon
I'm not sure why it wrote it the other way
Salomon
I got X =-6
Salomon
ok. so take the square root of both sides, now you have plus or minus the square root of 20= x-6
oops. ignore that.
so you not have an equal sign anywhere in the original equation?
Commplementary angles
hello
Sherica
im all ears I need to learn
Sherica
right! what he said ⤴⤴⤴
Tamia
what is a good calculator for all algebra; would a Casio fx 260 work with all algebra equations? please name the cheapest, thanks.
a perfect square v²+2v+_
kkk nice
algebra 2 Inequalities:If equation 2 = 0 it is an open set?
or infinite solutions?
Kim
The answer is neither. The function, 2 = 0 cannot exist. Hence, the function is undefined.
Al
y=10×
if |A| not equal to 0 and order of A is n prove that adj (adj A = |A|
rolling four fair dice and getting an even number an all four dice
Kristine 2*2*2=8
Differences Between Laspeyres and Paasche Indices
No. 7x -4y is simplified from 4x + (3y + 3x) -7y
is it 3×y ?
J, combine like terms 7x-4y
im not good at math so would this help me
yes
Asali
I'm not good at math so would you help me
Samantha
what is the problem that i will help you to self with?
Asali
how do you translate this in Algebraic Expressions
Need to simplify the expresin. 3/7 (x+y)-1/7 (x-1)=
. After 3 months on a diet, Lisa had lost 12% of her original weight. She lost 21 pounds. What was Lisa's original weight?
what's the easiest and fastest way to the synthesize AgNP?
China
Cied
types of nano material
I start with an easy one. carbon nanotubes woven into a long filament like a string
Porter
many many of nanotubes
Porter
what is the k.e before it land
Yasmin
what is the function of carbon nanotubes?
Cesar
what is nanomaterials​ and their applications of sensors.
what is nano technology
what is system testing?
preparation of nanomaterial
Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
what is system testing
what is the application of nanotechnology?
Stotaw
In this morden time nanotechnology used in many field . 1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc 2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc 3- Atomobile -MEMS, Coating on car etc. and may other field for details you can check at Google
Azam
anybody can imagine what will be happen after 100 years from now in nano tech world
Prasenjit
after 100 year this will be not nanotechnology maybe this technology name will be change . maybe aftet 100 year . we work on electron lable practically about its properties and behaviour by the different instruments
Azam
name doesn't matter , whatever it will be change... I'm taking about effect on circumstances of the microscopic world
Prasenjit
how hard could it be to apply nanotechnology against viral infections such HIV or Ebola?
Damian
silver nanoparticles could handle the job?
Damian
not now but maybe in future only AgNP maybe any other nanomaterials
Azam
can nanotechnology change the direction of the face of the world
At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
the Beer law works very well for dilute solutions but fails for very high concentrations. why?
how did you get the value of 2000N.What calculations are needed to arrive at it
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