Statistics as a Subject, Business Mathematics & Statistics Video Lecture | Business Mathematics and Statistics - B Com

hi if you're watching this video then
you're either taking a statistics course
or looking for more information about
statistics so what is it sistex
and is it complicated and I'm here to
tell you that no it's very easy to
understand it's very easy to interpret
and all you have to do is to really
understand the material by simplifying
when you took a look at your textbook
you might get overwhelmed by all the
information so simplify it and generally
you don't have to do that because I did
it for you in this video and the videos
to come so I'm here to tell you that you
can get an A+ or any mark you want since
that's all you have to do is simplify so
what are sadistic statistics is a way to
get information from that that's it so
you're thinking well if that's all it is
why is my textbook so large your
textbook is large because there's so
many ways to get information from data
and just be happy that you only have to
work with one textbook there are some
stations out there who work with many so
they have to simplify a lot of
information which takes a longer time
but ultimately it's very easy to
understand the specific definition of
stats is the mathematics of the
collection organization and
interpretation of numerical data the
second half of the definition don't
worry about it right now we'll describe
it later on in the video
the statistics branches off into two
main groups the first is descriptive
statistics
the second is inferential statistics so
let's describe the first descriptive
statistics means to describe the key
word is describe a phenomena a phenomena
I don't know how to say that word
summary and presentation of data and
what this means is well was what does it
mean when someone's summary someone
presents a summary and presentation well
think about when someone's up there is
some sort of a conference presenting
their have charts and they have
I charge and they have bar charts and I
have all these different visual
understandings of the material and
that's what it means for descriptive
statistics and inferential statistics on
the other hand is to draw conclusions
making four statements or predictions
about the population based on
statistical information so let's talk
about population population is a group
of all objects or individuals of
interest for example all objects of
interest can be all the students at the
University of Toronto all the students
at the University of York all the cats
in Canada these are all examples of
population a sample would be only the
cats and Toronto only the cats in New
York which is a subset of the population
that's all those that's all it really is
for those two terms so parameter sensor
systems
we generally we can say that populations
are described by parametres sample are
described by statistics and what does it
mean what it will what does it mean for
a parameter for example parameter the
average hair length of all domestic cats
reflects the true value of the
population statistics the average hair
length of cats in my sample it's an
estimate so statistical inference is
then the process of drawing a conclusion
about the population based on the sample
with certain levels of confidence and
significance I'll give you an example
over ramen in Japan what I mean by ramen
is all the stores in Japan myself on it
so if I wanted to know all the ramen in
Japan more amazing ramen or the big they
differentiate was one better than me and
how am I going to figure that out so I'm
going to take a sample I'm with it
either using how we're going to talk
about how we pick a sample later on I'm
going to pick that sample and through
the sample if the sample comes out
they're all wrong we are amazing I then
make an inference that all ramen in
Japan were amazing and that's what it
means it's the
conclusion about the population based on
the sample will talk about contents and
significance later on so a variable a
variable is a characteristics of a
population or sample and this is very
different from a parameter populations
are described by parameters there's a
difference in that a variable is the
characteristics of a population or
sample whereas parameter only refers to
population and an example of this is
student grades height income etc
variables have values and this is very
important because student grades for
example can we'll use this as an example
student grades zero one two three four
five to 100 100 being the highest so the
value is then a numerical numerical
representation and what this means is
the value is number it has to be a
number to describe a variable and data
is the observed values of variables the
example given here is student marks so
someone could have gone to seven someone
beside them at 73 I would have gotten s
md1 someone over there and 83 someone in
the front to 93 etc etc so they're
basically for the same digital reign
that's how you have to interpret data
data kind of looks like that there are
the observed values of variables and
that's really all it is now how do we
obtain the data is it hard no it's not
hard it's very easy to do and there is
two ways we can do it we can directly
collect the data which means we can do
it and this is called primary data
that means well it's it's very it's
self-definition primary data it's its
primary it's the first form of data
that's collected so its primary that's
why it's called primary day the second
way is we can use the data collected by
others in example statistics Canada or a
market research companies this is called
secondary data and there's just two ways
and that's rural it is now they've
branched off and let's start with the
first how do we collect primary data
there's three ways to do it by
observation by experiment or by survey
an example of observation is if I wanted
to know how many students at the
University of Toronto or our blue shirts
now I would certain one of the halls and
I would observe with my eyes all of the
blue shirts and I would write certain
things down there I could do by
experiment I can experiment by getting
large amounts of resources and this gets
more expressive or I can do it by survey
I can send out forms and if you were a
blue shirt you sign the form now all of
these is the difference in ingenta is
generally in the amount of control so
the difference is generally in the
amount of control exercised by the
researcher and the strength of it in
France that can be made so if all I did
was sit and observe and some home some
university who wore a blue shirt is that
enough to make an inference on the
entire population probably not I would
probably have to take a much more
thorough examination and this is what it
means by the amount of control so that's
primary data and decisions involving
involved in sampling so sample
population sample size and sample method
sample population from which population
do we sample lies it's important what do
we have to consider so you have to ask
yourself those questions when you're
thinking about making a sample or
analyzing a question with the population
sample size how large should the sample
be should be really large well that
takes more money
should it be small but then if it's too
small we can't make a you know the
inference won't be as strong to the
population the sampling method how
should we pick the sample out of the
population there's so many ways and it
can depend on many things so the size of
the population the sample size will
increase with the population size now I
advise you to write these things down
because the four that I'm going to
mention now are very important in
understanding what population and the
relationship between population and
sample so the sample size will increase
with the population size what that means
is if the population increases as shown
in the diagram by the second large
circle what also increases the sample
the variation in the population a
variation can be high a class middle
class and pork and low class and what
that means is that if there's too much
high class people and one in an entire
population we have to consider well this
population and the sample we take out of
it might be bias so if the variation
changes we have to change the size of
the population so we're going to have to
make sure that there is an adequate
amount of everything in there so the
sample size will increase with the
variation the third the amount of error
that can be tolerated and this is gets
very confusing for some students but
don't worry it's very easy
understand the amount of error that can
be tolerated in a sample and population
size in a sample size since our sample
size will decrease with this accepted
error so what does that mean the sample
size will decrease with the accepted
error what that means is the more
mistakes there are at a sample the
smaller it's going to get the amount of
resource available and this last one the
amount of resource available the sample
size will increase because you ought to
think about it if I have more money to
spend on making sure my sample is
accurate to the population I probably
spend that money and that's what it
means for resource do you have your
research team do you have your the
professionals will be out there speaking
to people surveying others that's what
that means so how do we create the
sample