Sampling Distribution and Statistics

Sampling distribution and statistics play crucial roles in the field of data analysis and inferential statistics. The sampling distribution is a fundamental concept that examines the distribution of a statistic, such as the mean or proportion, obtained from multiple samples of a population. Understanding the characteristics of sampling distributions is essential for making inferences about population parameters. Statistics, on the other hand, provide the tools and techniques to analyze and interpret data, enabling researchers and analysts to draw meaningful conclusions from samples and make informed decisions in various domains, from scientific research to business analytics.

Questions
  • What is the probability that the sample mean will be below 0.95 centimeters?
  • What does population distribution mean?
  • You take a sample of 144 observations and have a value of x bar equal to 59. The population mean is 68 and the population standard deviation is 36. What is the z score of your sample mean?
  • What is the Z-score for which 90% of the distribution's area lies between -z and z?
  • A population 1000 students spends an average of $10.50 on dinner. The standard deviation is $3. A simple random sample of 64 students is taken. What are the expected value and standard deviation of the sampling distribution of the sample mean?
  • Given a normal distribution with mean = 100 and standard deviation = 10, if you select a sample of n = 25, what is the probability that x-bar is less than 95?
  • Is a "spoonful of sugar" a population or sample?
  • Suppose a random sample of size 50 is selected from a population with σ = 10. What is the value of the standard error of the mean if the population size is 50?
  • As sample size increases, what happens to the standard error of M?
  • For a continuous random variable x, the population mean and standard deviation are 120 and 15 respectively. How do you find the mean and standard deviation of the sampling distribution of the sample mean for a sample of 25 elements?
  • Assume that the heights of women are normally distributed with a mean of 63.3 inches and a standard deviation of 2.5 inches. Seventy five women are randomly selected. What is the mean of the sample means?
  • A Population follows a normal distribution with mean 10 and standard deviation 2. In a sample of 100, what is the probability of the sample mean being between 9.5 and 10.1?
  • Is the sample mean equal to the population mean?
  • What's the difference between the population mean of a variable, the distribution of sample means of a variable, and the mean of a variable?
  • A population distribution has mean 50 and standard deviation 20. For a random sample of size 100, what is the mean and standard error of the sampling distribution of the sample mean?
  • What is the mean of the sampling distribution of the sample mean #x# if a sample of 64 students is selected at random from the entire freshman class?
  • A spinner has 5 equal sections labeled 1-5. In 60 spins, how often can you expect to see a 3?
  • Which statement is true about the population of the town?
  • The first sample mean distribution is based on samples of size n=100 and the second is based on sample of size n=225. Which sample mean distribution has the smaller standard error? Why?
  • When #n# is small (less than 30), how does the shape of the #t# distribution compare to the normal distribution?