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ne what is:
meter
mate
rentiate
nt estimate
erval
e
ective
:
- a numerica
characteristic
population, a
from a statisti
sample.
Parameter
Ex.
1. A number of students in CKC
2. A number of population in Brgy.
Matobato
Parameter
ue, or range
alues, that
roximates
population
Estimate
2 Types
Point Estimate
• It is a specific
numerical value of a
population parameter
• The sample mean 𝑋 is
the best point
estimate of a
population mean.
Interval Estimate
• Also called as
confidence interval, a
range values used to
estimate a parameter.
This estimate may or
may not contain the
true parameter value.
Point Estimate
Ex.
Jacky wanted to know
the average students
in statistics. She
interviewed 40
students and the
results are shown on
the right.
Interval Estimate
• When σ is known
The confidence level of an interval estimate is the
probability that the interval estimate will contain
the true population parameter.
- How sure are we that the population
parameter is really within that we came up with.
Interval Estimate – 2 ways
1.) When σ is known
The confidence level of an interval estimate is the
probability that the interval estimate will contain
the true population parameter.
- How sure are we that the population
parameter is really within that we came up with.
Interval Estimate – 2 ways
2.) When σ is unknown
When σ is unknown, the interval estimate can be
determined using the student’s t-distribution.
Interval Estimate: σ is known
Interval Estimate
E – Margin of Error
Z - critical value/z- value
σ – population standard deviation or sigma
N – sample size
Interval Estimate
Lower limit
Upper Limit
Solve for Interval Estimate
Example:
Step 1: Determine the given values
Step 2: Determine the critical value
Step 3: Solve for the margin of error using the formula
Step 4: Solve for the Interval estimate
Procedure:
Solve for Interval Estimate
Example:
Given:
Sample size (n) = 100
Sample mean 𝑿 = 150
Population SD σ = 40
Confidence level = 95% = critical value: Z =1.96
Solve for Interval Estimate
Example:
Given:
Sample size (n) = 50
Sample mean 𝑿 = 20.5
Population SD σ = 3.7
Confidence level = 99% = critical value: Z = 2.58
Interval Estimate – #2 way/ method
2.) When σ is unknown
When σ is unknown, the interval estimate can be
determined using the
student’s t-distribution.
Interval Estimate – σ is unknown
Where; n – is the sample size
Interval Estimate – σ is unknown
Interval Estimate – σ is unknown (Example)
Step 1: Determine the given values
Step 2: Determine the degrees of freedom using the formula
and the t (using the table)
Step 3: Solve for the margin of error using the formula
Step 4: Solve for the Interval estimate
Procedure:
Interval Estimate – σ is unknown (Example)
Given:
Sample size (n) = 30
Sample mean 𝑿 = 5.3
Sample S = 1.1
Confidence level = 95%
Degrees of freedom = n – 1 = 30 – 1 = 29
Interval Estimate – σ is unknown (Example)
ESTIMATING SAMPLE SIZE
In order to determine the sample size we follow
the formula:
n = [
𝑍𝑎
2
σ
𝐸
]2
Where;
n = sample size
𝒁𝒂
𝟐
= Z values
E = margin error
ESTIMATING SAMPLE SIZE
In order to determine the sample size we follow
the formula:
n = [
𝑍𝑎
2
σ
𝐸
]2
Where;
n = sample size
𝒁𝒂
𝟐
= Z values
E = margin error
QUIZ !!!
1 whole sheet of paper
-YES, 1 whole
Direction: Solve for the Point Estimate
95 85 85 90 88 80
88 87 82 92 90 91
88 94 90 92 89 90
96 89 84 90 85 87
95 96 94 93 94 90
89 88 89 85 86 92
Mr. Gonzales wanted to know the average students in
statistics. He interviewed 36 students and the results
are shown below.
Direction: Solve for the Interval Estimate.
In a study of 80 junior high school students, the mean number
of hours per week that they used internet was 40 hours. It was
estimated that the population standard deviation was 2.5. What
is the 95% confidence interval for the mean time for using
internet?
THANK YOU !!!

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Point and Interval Estimate by regi.pptx

  • 1.
  • 2. ne what is: meter mate rentiate nt estimate erval e ective :
  • 3. - a numerica characteristic population, a from a statisti sample. Parameter
  • 4. Ex. 1. A number of students in CKC 2. A number of population in Brgy. Matobato Parameter
  • 5. ue, or range alues, that roximates population Estimate
  • 6. 2 Types Point Estimate • It is a specific numerical value of a population parameter • The sample mean 𝑋 is the best point estimate of a population mean. Interval Estimate • Also called as confidence interval, a range values used to estimate a parameter. This estimate may or may not contain the true parameter value.
  • 7. Point Estimate Ex. Jacky wanted to know the average students in statistics. She interviewed 40 students and the results are shown on the right.
  • 8. Interval Estimate • When σ is known The confidence level of an interval estimate is the probability that the interval estimate will contain the true population parameter. - How sure are we that the population parameter is really within that we came up with.
  • 9. Interval Estimate – 2 ways 1.) When σ is known The confidence level of an interval estimate is the probability that the interval estimate will contain the true population parameter. - How sure are we that the population parameter is really within that we came up with.
  • 10. Interval Estimate – 2 ways 2.) When σ is unknown When σ is unknown, the interval estimate can be determined using the student’s t-distribution.
  • 12. Interval Estimate E – Margin of Error Z - critical value/z- value σ – population standard deviation or sigma N – sample size
  • 14. Solve for Interval Estimate Example: Step 1: Determine the given values Step 2: Determine the critical value Step 3: Solve for the margin of error using the formula Step 4: Solve for the Interval estimate Procedure:
  • 15. Solve for Interval Estimate Example: Given: Sample size (n) = 100 Sample mean 𝑿 = 150 Population SD σ = 40 Confidence level = 95% = critical value: Z =1.96
  • 16. Solve for Interval Estimate Example: Given: Sample size (n) = 50 Sample mean 𝑿 = 20.5 Population SD σ = 3.7 Confidence level = 99% = critical value: Z = 2.58
  • 17. Interval Estimate – #2 way/ method 2.) When σ is unknown When σ is unknown, the interval estimate can be determined using the student’s t-distribution.
  • 18. Interval Estimate – σ is unknown Where; n – is the sample size
  • 19. Interval Estimate – σ is unknown
  • 20. Interval Estimate – σ is unknown (Example) Step 1: Determine the given values Step 2: Determine the degrees of freedom using the formula and the t (using the table) Step 3: Solve for the margin of error using the formula Step 4: Solve for the Interval estimate Procedure:
  • 21. Interval Estimate – σ is unknown (Example) Given: Sample size (n) = 30 Sample mean 𝑿 = 5.3 Sample S = 1.1 Confidence level = 95% Degrees of freedom = n – 1 = 30 – 1 = 29
  • 22. Interval Estimate – σ is unknown (Example)
  • 23. ESTIMATING SAMPLE SIZE In order to determine the sample size we follow the formula: n = [ 𝑍𝑎 2 σ 𝐸 ]2 Where; n = sample size 𝒁𝒂 𝟐 = Z values E = margin error
  • 24. ESTIMATING SAMPLE SIZE In order to determine the sample size we follow the formula: n = [ 𝑍𝑎 2 σ 𝐸 ]2 Where; n = sample size 𝒁𝒂 𝟐 = Z values E = margin error
  • 25. QUIZ !!! 1 whole sheet of paper -YES, 1 whole
  • 26. Direction: Solve for the Point Estimate 95 85 85 90 88 80 88 87 82 92 90 91 88 94 90 92 89 90 96 89 84 90 85 87 95 96 94 93 94 90 89 88 89 85 86 92 Mr. Gonzales wanted to know the average students in statistics. He interviewed 36 students and the results are shown below.
  • 27. Direction: Solve for the Interval Estimate. In a study of 80 junior high school students, the mean number of hours per week that they used internet was 40 hours. It was estimated that the population standard deviation was 2.5. What is the 95% confidence interval for the mean time for using internet?