CHAPTER: 11
STATISTICS
By: Raiyah and
Adrienne
BIAS AND USE OF LANGUAGE
 If a company is bias towards their product it’ll make the
consumers want to buy their product over any other
competitor.
 Using bias language can influence the decision of a
costumer. If a costumer is deciding between multiple
products and one competitor uses bias language it gives
them an edge on other competitors because it convinces
the costumer to buy their product.
 Using specific language can change the way a question is
received by the costumers which with also influence their
decision on which product to buy.
COST
 The cost of a product can influence a decision by the
costumer if the cost is lower than a competitors.
 Distributers use specific language before the price of their
product to make it seem like there’s a deal when really there
isn’t. Ex. “Price as low as” or “for a limited time only.”
TIME AND TIMING
 If a distr ibuter is tr ying to sell a product or get a statistic f or
which product is best they use timing wisely to get an accurate
response or a response that they want.
 For example: if a distr ibuter wants
school supplies has the most sales,
research in August and September,
school is almost over and no one is
a statistic on which brand of
they would do they’re
not in March or Apr il when
buying.
PRIVACY
 If a creator of the survey wants to ask people their opinion
on a certain topic but not all of the people who were asked
want to respond so that can throw off a statistic.
 Example: T he gover nement wants to do a sur vey to see how many
people are voting f or Donald Tr ump so they ask 50 people who they
are voting f or. Only 25 respond saying that they are voting f or Donald
but they other half don’t give a response because they don ’t f eel
comf or ta ble revealing that inf ormation. So unless the gover nement
states that only 25 people responded the statistic gives off an incorrect
impression.
CULTURAL SENSITIVITY
 Sometimes peoples religions can help influence a decision,
because if you are using bias opinion to hint towards an answer
that is religious, lets say related to god, and the other answer is
related to the devil, they will chose the one with god!
Sometimes questions can off end cer tain religions, such as 90%
of people agree that C hr istians are the most believable. Also
the data collectors can ask cer tain religions f or a cer tain result.
POPULATION VS. SAMPLE
 I n s t a t i s t ic s p o p u l at io n s i s a wo rd u s e d t o d e s c r ib e t h e e n t i re
ove ra l l g ro u p yo u a re t r y i n g t o re c e ive i n f o r m at i o n f ro m . S a m p l e i s
t h e a c t u al a m o u nt o f p e o p l e o r t h i n g s yo u re c e ive d i n f o r m at i on
f ro m . S a m pl e i s u s e d t o re p re s e n t t h e e n t i re p o p u l at i o n .
 E x a m pl e : wh e n yo u re c e ive a s a m pl e p ro d u c t , i t i s a s a m p le
b e c au se i t i s o n ly a s m a l l p o r t i o n u s e d t o re p re s e n t a n d s h ow wh a t
t h e re s t o f t h e p ro d u c t i s l i ke. S a m e t h i n g i n s t a t i s t i c s, t h e s a m p l e
yo u re c e ive d d a t a f ro m , i s s u p po s e d t o re p re s e n t wh a t t h e e n t i re
p o p u l at i o n t h i n k s .
 E x a m pl e 2 : i f yo u a re t r y i n g t o f i n d h ow m a ny d e n t i s ts re c o mm e n d a
b ra n d , yo u wa n t t o k n ow f ro m a l l t h e d e n t i s t s ( t h e p o p u l at i o n ) , b u t i f
yo u d o n ' t h ave t h e f u n d s o r t h e a b i l i t y t o d o s o, yo u c a n a s k a
p o r t i o n o f d e n t i s t s ( a s a m p l e ) t h e i r o p i n i o n , a n d u s e t h a t t o ge t a n
e s t i m at e o f wh at t h e wh o l e p o p u l at io n t h i n k s
SAMPLING METHODS
 CONVENIENCE SAMPLE:
I s s a m p l i n g d o n e i n t h e m o s t c o nve n i e n t way t o
t h e re s e a rc h e r, i t ’s s a m p l i n g t h e g ro u p w i t h t h e e a s i e s t a c c e s s t o t h e m . E x . I f t h e
re s e a rc h e r wa n t s t h e o p i n i o n o f t h e p o p u l a t i o n o f t e a c h e r s t h ey wo u l d a s k t h e
teachers at the school closest to them.
 RANDOM SAMPLE:
I s s a m p l i n g d o n e by c h o o s i n g ra n d o m s u b j e c t s t o b e a
p a r t o f t h e s a m p l e. A nyo n e t h a t q u a l i f i e s h a s t h e s a m e a m o u n t o f c h a n c e t o b e
c h o s e n . E x . I f yo u wa n t t o k n ow wh a t f o o d t h e c a f e t e r i a s h o u l d s e r ve a t l u n c h yo u
c o u l d a s k a ny s t u d e n t a t ra n d o m a n d i t wo u l d n ’t m a t t e r.
 STRATIFIED SAMPLE: I s s a m p l in g t a rge t i n g s p e c i f i c g ro u p s o f p e o p l e
i n s t e ad o f c ro s s s e c t i o n s . E x . I f t h e g ro u p wa s c h i l d re n u n d e r t h e a ge o f 7 a n d
re s e arc h e r s a s ke d wh a t i s t h e i r f avo r i t e h o bby t h e re s u l t m ay b e c o l o r i n g, b u t
t h a t ’s o n ly b e c au se t h ey a s ke d a s p e c i f ic g ro u p i f p e o p l e t o ge t a s p e c i f i c
re s p o n s e.
 SYSTEMATIC SAMPLE : I s s a m pl i n g t h a t a l l ows yo u t o i n c l u d e m o re
p e o p l e i n t h e t e s t i n g b u t o n ly s u r vey i n g a s y s t e mat i c al ly c h o s e n g ro u p o r
n u m b e r o f p e o p l e. E x . T h e re i s a s u r vey o f 1 0 0 0 p e o p l e e x c ept yo u o n ly u s e t h e
d a t a f ro m eve r y 1 0 t h p e r s o n .
 VOLUNTARY RESPONSE SAMPLE: I s s a m p l i n g wh e re t h e s a m p l e r s
vo l u n t e e r t o b e a p a r t o f t h e p o l l . E x . A n ew s s h ow a s k s v i ewe r s t o p a r t i c ip at e
i n a n o n - l i n e p o l l . T h e s a m pl e i s c h o s e n by t h e v i ewe r s , n o t by t h e p e o p l e
s u r vey i n g.
INAPPROPRIATE SAMPLING METHODS
 If a distributer uses an inappropriate method of sampling
it could throw off the message the distributer is trying to
convey to the consumers.
 Example #1:
I f t h e re was a s ur vey t o s e e wh ic h f as t f o o d re s t auran t
was t h e m o s t p o p ular but t h ey us e d a s t rat if ie d s am p le o f p e o p le wh o wo rk
at Mc D o n ald ’s t o ge t a c e r t ain re s p o n se.
 Example #2:
I f t h e s ur vey was t o s e e wh ic h s ub je c t in s c h o o l was t h e
m o s t p o p ular but t h e d is t r ibut e r us e s vo lun t ar y s am p lin g an d n o n e o f t h e
vo lun t ee rs are in s c h o o l s o t h e d is t r ibut er wo n ’t ge t an ac c urat e re s p o n s e.
EXPERIMENTAL VS. THEORETICAL
 An example is when you flip a coin ten times. Theoretically
you expect the coin to long on each side 5 times. Because
there is a 50 50 chance so the theoretical statistic is 50%
on each side. Experiments is the actual outcome of the test
based on the amount of times you flipped the coin. What is
supposed to happen VS what actually does happen
EXAMPLE #1
WHAT’S WRONG WITH THIS STATISTIC?
1. The chart makes Chevy seem like the obvious
option to choose when in reality if you pay
attention Chevy is only 1% higher than Ford
and 3% more than Nissan but the chart makes
it look a lot higher.
2. We also don’t know if this statistic is for Chevys
all around the world or just from one
dealership.
3. We don’t know how popular Chevy was 10
years ago or how many they sold, also they
could have had more repairs and maintenance
done on them, the quality could be horrible
but the car could still run, they never said the
cars run smoothly.
EXAMPLE #2
WHAT’S WRONG WITH THIS STATISTIC?
1. This is an example of a population statistic,
obviously Maybelline couldn’t have asked
all of America which mascara they
preferred, so that is misleading.
2. We don’t know what the question
Maybelline asked to get these results. They
could’ve listed multiple mascaras and made
the consumers choose which one they
preferred.
EXAMPLE #3
WHAT’S WRONG WITH THIS STATISTIC?
1. We don’t know what the original question
was. Based on the information showed we
can assume there were only two options to
the question, either have homework or go
to school.
2. In the pie chart it says “do homework” but
in the question it’s self it says do
homework on Saturdays so by adding “on
Saturday” it makes the question more bias
and is favouriting a certain answer.