1. Illustrate point and interval estimations.
2. Distinguish between point and interval estimation.
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Hypothesis Testing is important part of research, based on hypothesis testing we can check the truth of presumes hypothesis (Research Statement or Research Methodology )
It includes various cases and practice problems related to Binomial, Poisson & Normal Distributions. Detailed information on where tp use which probability.
A Probability Distribution is a way to shape the sample data to make predictions and draw conclusions about an entire population. It refers to the frequency at which some events or experiments occur. It helps finding all the possible values a random variable can take between the minimum and maximum statistically possible values.
1. Illustrate point and interval estimations.
2. Distinguish between point and interval estimation.
Visit the website for more services it can offer:
https://cristinamontenegro92.wixsite.com/onevs
Hypothesis Testing is important part of research, based on hypothesis testing we can check the truth of presumes hypothesis (Research Statement or Research Methodology )
It includes various cases and practice problems related to Binomial, Poisson & Normal Distributions. Detailed information on where tp use which probability.
A Probability Distribution is a way to shape the sample data to make predictions and draw conclusions about an entire population. It refers to the frequency at which some events or experiments occur. It helps finding all the possible values a random variable can take between the minimum and maximum statistically possible values.
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Chapter 6: Normal Probability Distribution
6.3: Sampling Distributions and Estimators
Lecture 5 Sampling distribution of sample mean.pptxshakirRahman10
Objectives:
Distinguish between the distribution of population and distribution of its sample means
Explain the importance of central limit
theorem
Compute and interpret the standard error of the mean.
Sampling distribution of
sample mean:
A population is a collection or a set of measurements of interest to the researcher. For example a researcher may be interested in studying the income of households in Karachi. The measurement of interest is income of each household in Karachi and the population is a list of all households in Karachi and their incomes.
Any subset of the population is called a sample from the population. A sample of ‘n’ measurements selected from a population is said to be a random sample if every different sample of size ‘n’ from the population is equally likelyto be selected.
For the purpose of estimation of certain characteristics in the population we would like to select a random sample to be a good representative of the population.
The set of measurements in the population may be summarized by a descriptive characteristic, called a parameter. In the above example the average income of households would be the parameter.
The set of measurements in a sample may be summarized by a descriptive statistic, called a statistic . For example to estimate the average household income in Karachi, we take a random sample of the population in Karachi. The sample mean is a statistic and is an estimate of the population mean.
Because no one sample is exactly like the next , the sample mean will vary from sample to sample ,and hence is itself a random variable.
Random variables have distribution ,and since the sample mean is a random variable it must have a distribution.
If the sample mean has a normal distribution ,we can compute probabilities for specific events using the properties of the normal distribution.
Consider the population with population mean = μ
and standard deviation = σ.
Next, we take many samples of size n, calculate the mean for each one of them, and create a distribution of the sample means.
This distribution is called the Sampling Distribution of Means.
Technically, a sampling distribution of a statistic is the distribution of values of the statistic in all possible samples of the same size from the same population.
Standard error of the
mean:
The quantity σ is referred to as the standard deviation .it is a measure of spread in the population .
The quality σ/n is referred to as the standard error of the sample mean .It is a measure of spread in the distribution of mean
A very important result of statistics referring to the sampling distribution of the sample mean is the Central Limit Theorem .
Central Limit Theorem:
Consider a population with finite mean and standard deviation . If random samples of n measurements are repeatedly drawn from the population then, when n is large, the relative frequency histogram for the sample means ( calculated from repeated samples)
Brgy. Labangon, Cebu City and the Threat to its Territorial IntegrityHarve Abella
the people have spoken, NO to the creation of Banawa-Englis.
by the way, Tony Cuenco (author of the Banawa-Englis law fiasco) has bowed out of the congressional race (or so he claims.) do we really need recycled politicians???
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Welcome to the new Mizzima Weekly !
Mizzima Media Group is pleased to announce the relaunch of Mizzima Weekly. Mizzima is dedicated to helping our readers and viewers keep up to date on the latest developments in Myanmar and related to Myanmar by offering analysis and insight into the subjects that matter. Our websites and our social media channels provide readers and viewers with up-to-the-minute and up-to-date news, which we don’t necessarily need to replicate in our Mizzima Weekly magazine. But where we see a gap is in providing more analysis, insight and in-depth coverage of Myanmar, that is of particular interest to a range of readers.
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Navigating the Future of Fintech in India: Insights into how AI, blockchain, and digital payments are driving unprecedented growth in India's fintech industry, redefining financial services and accessibility.
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role of women and girls in various terror groupssadiakorobi2
Women have three distinct types of involvement: direct involvement in terrorist acts; enabling of others to commit such acts; and facilitating the disengagement of others from violent or extremist groups.
In a May 9, 2024 paper, Juri Opitz from the University of Zurich, along with Shira Wein and Nathan Schneider form Georgetown University, discussed the importance of linguistic expertise in natural language processing (NLP) in an era dominated by large language models (LLMs).
The authors explained that while machine translation (MT) previously relied heavily on linguists, the landscape has shifted. “Linguistics is no longer front and center in the way we build NLP systems,” they said. With the emergence of LLMs, which can generate fluent text without the need for specialized modules to handle grammar or semantic coherence, the need for linguistic expertise in NLP is being questioned.
हम आग्रह करते हैं कि जो भी सत्ता में आए, वह संविधान का पालन करे, उसकी रक्षा करे और उसे बनाए रखे।" प्रस्ताव में कुल तीन प्रमुख हस्तक्षेप और उनके तंत्र भी प्रस्तुत किए गए। पहला हस्तक्षेप स्वतंत्र मीडिया को प्रोत्साहित करके, वास्तविकता पर आधारित काउंटर नैरेटिव का निर्माण करके और सत्तारूढ़ सरकार द्वारा नियोजित मनोवैज्ञानिक हेरफेर की रणनीति का मुकाबला करके लोगों द्वारा निर्धारित कथा को बनाए रखना और उस पर कार्यकरना था।
‘वोटर्स विल मस्ट प्रीवेल’ (मतदाताओं को जीतना होगा) अभियान द्वारा जारी हेल्पलाइन नंबर, 4 जून को सुबह 7 बजे से दोपहर 12 बजे तक मतगणना प्रक्रिया में कहीं भी किसी भी तरह के उल्लंघन की रिपोर्ट करने के लिए खुला रहेगा।
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Yeduguri Sandinti Jagan Mohan Reddy, often referred to as Y.S. Jagan Mohan Reddy, is an Indian politician who currently serves as the Chief Minister of the state of Andhra Pradesh. He was born on December 21, 1972, in Pulivendula, Andhra Pradesh, to Yeduguri Sandinti Rajasekhara Reddy (popularly known as YSR), a former Chief Minister of Andhra Pradesh, and Y.S. Vijayamma.
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1. Definition: A sampling distribution of sample means is a distribution obtained by using the means computed from random samples of a specific size taken from a population. Remark: If the samples are randomly selected, the sample means will be somewhat different from the population mean . These differences are caused by sampling error. Definition: Sampling Error is the difference between the sample measure and the corresponding population measure due to the fact that the sample is not a perfect representation of the population.
2. Properties of the Distribution of Sample Means 1. The mean of the sample means will be the same as the population mean. 2. The standard deviation of the sample means will be smaller than the standard deviation of the population, and it will be equal to the population standard deviation divided by the square root of the sample size, that is,
3. Example: Suppose a professor gave an eight point quiz to a small class of 4 students. The results of the quiz were 2, 6, 4 and 8. For the sake of discussion, assume that the four students constitute the population. The mean of the population is The standard deviation of the population is
4. The graph of the original distribution is shown as follows which is called a uniform distribution. Now, if all samples of size 2 are taken with replacement, and the mean of each sample is found, the distribution is as follows:
5. Now, if all samples of size 2 are taken with replacement, and the mean of each sample is found, the distribution is as follows: Sample Mean Sample Mean 2,2 2 6, 2 4 2,4 3 6, 4 5 2,6 4 6, 6 6 2,8 5 6, 8 7 4, 2 3 8, 2 5 4, 4 4 8, 4 6 4, 6 5 8, 6 7 4, 8 6 8, 8 8
7. The following shows the graph of the sample means which appears to be somewhat normal, even though it is a histogram.
8. The mean of the sample means, denoted by which is the same as the population mean. The standard deviation of sample mean, denoted by which is the same as the population standard deviation divided by , that is,
