excel and correlation

Summary

In 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

00:00

📚 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.

05:01

📊 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.

Keywords

💡Instructor

The term 'instructor' refers to a person who teaches or gives instruction, often in a professional or academic setting. In the video's context, Doctor Samuel Keshwa is the instructor, leading the lesson on statistical correlation. His role is central to the video's educational theme, as he guides students through the concept of correlation.

💡Correlation

Correlation is a statistical term that describes a relationship between two variables. In the video, Doctor Keshwa explains that correlation measures the strength and direction of the relationship between an independent variable and a dependent variable. The script uses examples like the relationship between temperature and ice cream sales to illustrate this concept.

💡Independent Variable

An independent variable is a variable that is thought to influence the dependent variable without being affected by it. In the script, temperature is used as an example of an independent variable because it is assumed to influence ice cream sales without being influenced by them.

💡Dependent Variable

A dependent variable is one that is affected by changes in the independent variable. In the video, ice cream sales are the dependent variable because they are thought to change in response to changes in temperature, the independent variable.

💡Positive Relationship

A positive relationship in statistics means that as one variable increases, the other variable also increases. Doctor Keshwa explains this by stating that higher temperatures lead to increased ice cream sales, indicating a positive correlation.

💡Correlation Coefficient

The correlation coefficient is a numerical value that represents the strength and direction of the relationship between two variables. In the script, the coefficient of 0.875 is mentioned, indicating a strong positive relationship between temperature and ice cream sales.

💡Spreadsheets

Spreadsheets are computer applications used for data organization, analysis, and management. In the video, Doctor Keshwa demonstrates how to use spreadsheets, specifically Microsoft Excel, to calculate and understand statistical correlations.

💡Excel

Excel is a widely used spreadsheet program developed by Microsoft. The script shows how to import data into Excel and use its functions to calculate the correlation coefficient, emphasizing the practical application of statistical concepts in business and data analysis.

💡Statistical Functions

Statistical functions in Excel are tools that perform various statistical calculations, such as calculating the correlation coefficient. Doctor Keshwa guides the students through using the 'CORREL' function in Excel to find the correlation between temperature and ice cream sales.

💡Paste Special

Paste Special is a feature in Excel that allows users to import data from other applications while maintaining the original formatting. In the script, Doctor Keshwa uses Paste Special to import a table from Microsoft Word into Excel, demonstrating a common data management technique.

💡HTML

HTML, or HyperText Markup Language, is used for creating and designing web pages. In the script, Doctor Keshwa selects 'HTML' when using Paste Special, which indicates that the data from Word is being imported with its original web-friendly formatting into Excel.

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