excel and correlation
Summary
TLDRIn this educational video, Dr. Samuel Keshwa introduces the concept of statistical correlation, explaining the relationship between independent and dependent variables using relatable examples like price and quantity demanded, and temperature and ice cream sales. He demonstrates how to calculate the correlation coefficient using a spreadsheet, highlighting the strong positive correlation between temperature and ice cream sales with a coefficient of 0.875, emphasizing the direct relationship and its significance in understanding variable interactions.
Takeaways
- 👨🏫 The instructor, Dr. Samuel Keshwa, introduces the concept of statistical correlation, emphasizing its importance in understanding relationships between variables.
- 🔍 Correlation is defined as the study of the relationship between two variables, specifically the independent variable that affects and the dependent variable that is affected.
- 📈 Examples given include the inverse relationship between price and quantity demanded, and the direct relationship between temperature and ice cream sales.
- 🌡️ Temperature is used as an independent variable example, affecting the dependent variable, ice cream sales, with higher temperatures leading to increased sales.
- 📊 The instructor demonstrates how to calculate the correlation coefficient using spreadsheets, specifically Microsoft Excel, to analyze the relationship between variables.
- 📋 The process of importing data into Excel from Microsoft Word is shown, highlighting the versatility of spreadsheets in handling various data formats.
- 🖥️ Excel functionalities such as formatting cells, adjusting column widths, and changing font styles are briefly explained to enhance data presentation.
- 🔢 The calculation of the correlation coefficient is performed using the CORREL function in Excel, with the instructor guiding through the selection of the correct data arrays.
- 📝 The correlation coefficient result of 0.875 is interpreted, indicating a strong positive relationship between the independent and dependent variables.
- 📉 A correlation coefficient greater than 0.5 signifies a strong relationship, while a value less than 0.5 indicates a weaker relationship.
- 📚 The importance of understanding correlation for analyzing business and statistical problems is emphasized, encouraging students to study the concept.
Q & A
What is the topic of the lecture given by Doctor Samuel Keshwa?
-The topic of the lecture is statistical correlation, focusing on the relationship between two variables, specifically the independent and dependent variables.
What does 'correlation' mean in the context of the lecture?
-In the lecture, 'correlation' refers to the type of relationship that exists between two variables, where one variable (independent) affects the other (dependent).
Can you provide an example of an independent variable from the lecture?
-An example of an independent variable given in the lecture is 'temperature,' which affects the sales of ice cream.
What is an example of a dependent variable mentioned in the lecture?
-The sales of ice cream are given as an example of a dependent variable, which is affected by the temperature (independent variable).
What is the significance of the correlation coefficient mentioned in the lecture?
-The correlation coefficient, in this case, 0.875, measures the strength and direction of the relationship between the independent and dependent variables. A value closer to 1 indicates a strong relationship.
What does a positive correlation coefficient indicate about the relationship between variables?
-A positive correlation coefficient, like the one mentioned in the lecture (0.875), indicates a direct relationship where an increase in the independent variable leads to an increase in the dependent variable.
How is the strength of the correlation determined in the lecture?
-The strength of the correlation is determined by the value of the correlation coefficient. A coefficient of 0.5 or more indicates a strong relationship.
What tool does Doctor Keshwa use to demonstrate the calculation of correlation in the lecture?
-Doctor Keshwa uses a spreadsheet application, specifically Microsoft Excel, to demonstrate the calculation of the correlation coefficient.
Can you explain how Doctor Keshwa imports data into Excel from Microsoft Word?
-Doctor Keshwa copies the data from Microsoft Word and then uses the 'Paste Special' feature in Excel, choosing HTML format to import the data.
What is the role of the spreadsheet in solving statistical problems according to the lecture?
-According to the lecture, spreadsheets are used to solve statistical problems by organizing and analyzing data, and they can be particularly useful in business contexts.
Why is it important to distinguish between independent and dependent variables when studying correlation?
-Distinguishing between independent and dependent variables is important because it helps to understand which variable is influencing the other, allowing for better analysis and prediction in statistical studies.
Outlines
📚 Introduction to Statistical Correlation
In this introductory lecture, Dr. Samuel Keshwa welcomes students to a lesson on statistical correlation. He explains the concept by using the example of the relationship between the price of a product and its quantity demanded, as well as the relationship between temperature and ice cream sales. He emphasizes the distinction between independent and dependent variables, using temperature as an independent variable that affects the dependent variable, ice cream sales. The instructor also demonstrates how to calculate the correlation coefficient using spreadsheets, specifically Microsoft Excel, and shows the process of importing data from Microsoft Word into Excel. The goal is to understand how these tools can be used to solve statistical problems in business.
📊 Calculating and Interpreting the Correlation Coefficient
Dr. Keshwa continues the lesson by guiding students through the process of calculating the correlation coefficient using Excel's statistical functions. He inputs the data for temperature and ice cream sales into the spreadsheet and applies the CORREL function to find the correlation between the two variables. The result, a coefficient of 0.875, indicates a strong positive relationship, meaning that as temperature increases, so do ice cream sales. The instructor clarifies that a positive correlation implies a direct relationship, where an increase in the independent variable (temperature) leads to an increase in the dependent variable (ice cream sales). He concludes by reinforcing the importance of understanding the correlation coefficient in analyzing the relationship between variables and encourages students to study the concept further.
Mindmap
Keywords
💡Instructor
💡Correlation
💡Independent Variable
💡Dependent Variable
💡Positive Relationship
💡Correlation Coefficient
💡Spreadsheets
💡Excel
💡Statistical Functions
💡Paste Special
💡HTML
Highlights
Introduction to the concept of statistical correlation by Dr. Samuel Keshwa.
Explanation of independent and dependent variables using examples like prices and quantity demanded.
Discussion on the relationship between temperature and ice cream sales.
Clarification that temperature is the independent variable while ice cream sales are the dependent variable.
Demonstration of how to calculate correlation using a spreadsheet.
Step-by-step guide on exporting a table from Microsoft Word to Excel.
Instruction on how to paste special in Excel and format the table.
Explanation of using Excel's statistical functions to find the correlation coefficient.
Detailed example of calculating correlation between temperature and ice cream sales data.
Interpretation of the correlation coefficient value 0.87 as a strong positive relationship.
Explanation that a correlation coefficient above 0.5 indicates a strong relationship.
Reiteration that the higher the temperature, the higher the ice cream sales.
Definition of correlation as a relationship between independent and dependent variables.
Conclusion emphasizing the importance of understanding correlation in statistical analysis.
Final remarks encouraging students to study the correlation and thanking them for their attention.
Transcripts
welcome my dear students uh this is your
instructor
uh doctor samuel keshwa and we will talk
today
about the correlation
statistical correlation
correlation c o r or e l a t
i o in correlation
collision means this is a kind of
relationship
what is the relationship to study the
relationship between
two variables we call them one of them
is called
independent variable and the other is
called
dependent variable uh
it's like an example the prices and the
quantity
demanded you know when the prices go up
the quantity demanded go down and also
the relationship between the temperature
and the ice cream sales
in the winter time we expect that the
sales of the ice cream
is lower than the summer time because
in the summer it's very hot so the sales
of the ice cream will increase
and vice versa by the way
so we call this the relationship between
two variables the independent variable
is always
affecting but it's not expected
it is affecting the independent so if we
say the relationship between the
temperature
and the ice cream seal sales then the
temperature will be the
independent variable while
the ice cream sales will be the
consequence
or the dependent variable
the independent is the temperature
nothing affects the temperature
but the temperature affect the sales
so the temperature is independent
variable and the sales of the ice
cream or pepsi or whatever is a
dependent
variable because it depends on the
temperature
let's go and see how we will calculate
the correlation and what is the
correlation coefficient
and what the meaning of what results we
will get
by our
curriculum we are getting use
of the spreadsheets in solving
problems statistical problems or
any kind of problems regarding the
business
how we will get use of this okay
we open now a new spreadsheet and like i
told you before let me close it back
and open it back in front of you so you
will go from the main menu here
and if you pin it here on the uh from
the start menu that's fine
if you didn't spin it you will get it
from the all programs you will find the
microsoft
so press one place like this go
okay this table i prepared in
a microsoft word but i can
can export it into the uh excel
yes i can export it how i'll stop on the
cross here look at this
wait a minute i will stop it across then
like this is able to be
copied now then click right
then copy then i will go to the excel
here we go i will stop in the excel and
cell a
one then i will say paste
special paste special
and i will go i won't select the first
one and second one i'll select
html html
perfect okay here we go here is our
own table which we draw already here
now it is on the excel with the same
characteristics nothing more nothing is
less
uh if i want as example to
enlarge like enlarge here enlarge
or widen the cell where are the mounts
and this
that's fine if i want as example to just
bowl them or write them in any kind of
line
here we go and here also if i want to
bold
the month let's see you got it so
we can do this and we can you can change
also the
type of lines uh like here is example
you want to make it time new romans or
calibri or algerian
see the way it is it goes based on what
you want are black or
ariel anything it goes like what you
want
anyhow this towards the start itself
of how we will get the correlation now i
want to get the correlation between the
two variables
between the temperature and between the
ice cream
well that's fine if i stop as example on
this cell
and go to effects let's see what will
happen
and i won't test the most recently or
you can get the statistical
statisticals will give you all the
statistical functions
from fx statisticals then i will go to
check out the correlation
and see here it is c-o-r-r-e-l
correlation angle okay i will say
array one from b
2 2 i
or to j 2 from b 2
to the last one is j 2
g2 array 2
is from b3
b3 to
uh j3
j three okay
so when i write it down he write to me
the numbers like i have here now he's
like confirming seven and six and eight
and nine and eighteen and twenty-two
and 24 and 27 and 19
this is the first cereal and the second
cereal
is uh here we go
50 60 70
80 85
95 110
150 and 80 that's perfect
that's fine yes that's what i want okay
then
i will say okay here is the correlation
what do you mean by 0.87.87
correlation we said is a relationship
between
the independent variables and the
dependent variables
here it is positive relationship because
we don't have a minus we don't have a
minus it's a positive
positive means there is a relationship
between the temperature and the ice
cream
so it's positive and it's a strong
relationship
strong why because look at this the
number is 0.8
which is more than
0.5 so 0.5 and more we call it a strong
relationship that means that the more
the higher the temperature the more
the sales of the ice cream again i will
say
the higher the temperature the more the
sales of the ice cream because the
coefficient of the correlation
is 0.875
which means that
it means that the sales are increased
when the when the temperature increase
not as please
that we said before we have independent
variable
that is the temperature independent
uh because this effect but it is not
affected
the temperature nothing affecting the
temperature
temperature affect the seeds of the ice
cream so the temperature
is independent variable
while the ice cream is dependent
variable
again we said the correlation i would
say the correlation
again the definition it is a
relationship between
independent variable and dependent
variables
but where it goes if it is positive
like this then it's a direct
relationship
direct relationship means that the more
the temperature the higher the
temperature the more the sales of the
ice cream
and vice versa the less the temperature
the less the sales of the ice cream
so the temperature is the independent
variable
and the ice cream is the dependent
variable
and the coefficient of correlation here
is 0.875
which means that it is a positive strong
relationship 0.5 or more
this is a strong relationship less than
0.5
is not a strong relationship yeah they
are increasing but not
with the same degree or was so uh
was so high like the increase in the
temperature
so this was the correlation please study
it
and thank you so much and have a good
night take care bye
you
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