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The t-distribution and the normal distribution are not exactly the same. The t-distribution is approximately normal, but since the sample size is so small, it is not exact. But n increases (sample size), degrees of freedom also increase (remember, df = n - 1) and the distribution of t becomes closer and closer to a normal distribution. Check out this picture for a visual explanation: http://www.uwsp.edu/PSYCH/stat/10/Image87.gif
What else can I help you with?
Why does a binomial distribution become more skewed as n increases?
As n increases, the distribution becomes more normal per the central limit theorem.
What is the definition of central limit theorem?
The central limit theorem basically states that as the sample size gets large enough, the sampling distribution becomes more normal regardless of the population distribution.
What is the earth's gravity in terms of acceleration?
9.8 m/s2 ---------------------- Yes this is the average value of acceleration due to gravity near by the surface of the earth. As we go higher and higher level this g value decreases and becomes almost negligible. Same way as we go deeper and deeper the g value decreases and at the centre of the earth its value becomes zero.
When do you use a z - table compared with when you use a t - table?
For statistical tests based on (Student's) t-distribution you use the t-table. This is appropriate for small sample sizes - up to around 30. For larger samples (or degrees of freedom), the t-distribution becomes very close to the Standard Normal distribution so you use the z-tables.
Does Chi-square distribution becomes more skewed as the degrees of freedom increase?
No- skewness parameter declines with increased degrees of freedom. skewness = sqrt(8/k) see link
What is the Difference between normal and gaussian distribution?
Actually the normal distribution is the sub form of Gaussian distribution.Gaussian distribution have 2 parameters, mean and variance.When there is zero mean and unit variance the Gaussian distribution becomes normal other wise it is pronounced as Gaussian.Wrong! The standard normal distribution has mean 0 and variance 1, but a normal distribution is the same as the Gaussiand, and can have any mean and variance. Google stackexcange "what-is-the-difference-between-a-normal-and-a-gaussian-distribution"
If two bodies of different mass fall from same height will they reach at the same time?
Yes - but only if you can ignore air resistance, that is, if the objects fall for a sufficiently short time, and have a sufficiently high mass, and sufficiently small surface area, so that air resistance becomes insignificant.Yes - but only if you can ignore air resistance, that is, if the objects fall for a sufficiently short time, and have a sufficiently high mass, and sufficiently small surface area, so that air resistance becomes insignificant.Yes - but only if you can ignore air resistance, that is, if the objects fall for a sufficiently short time, and have a sufficiently high mass, and sufficiently small surface area, so that air resistance becomes insignificant.Yes - but only if you can ignore air resistance, that is, if the objects fall for a sufficiently short time, and have a sufficiently high mass, and sufficiently small surface area, so that air resistance becomes insignificant.
What does slate turn into if heated and squashed?
If slate is sufficiently heated and compressed it becomes phyllite.
The Central Limit Theorem is important in statistics because?
According to the central limit theorem, as the sample size gets larger, the sampling distribution becomes closer to the Gaussian (Normal) regardless of the distribution of the original population. Equivalently, the sampling distribution of the means of a number of samples also becomes closer to the Gaussian distribution. This is the justification for using the Gaussian distribution for statistical procedures such as estimation and hypothesis testing.
Why does a binomial distribution become more skewed as n increases?
As n increases, the distribution becomes more normal per the central limit theorem.
Would an object have a greater gravitational pull closer or farther from earth?
An object have greater gravitational pull closer from earth. As we get farther from earth, the gravitational pull becomes weaker. That is why objects sufficiently away from the earth do not fall on it.
Does the t distribution becomes more skewed As the degree of freedom increases?
The t-distribution is symmetric so the question is irrelevant.The t-distribution is symmetric so the question is irrelevant.The t-distribution is symmetric so the question is irrelevant.The t-distribution is symmetric so the question is irrelevant.
What is the difference between a star that becomes a red giant and one that becomes a red supergaint?
The mass of the star.
How does decreasing the temperature affect the value of a gas?
Generally speaking - if you lower the temperature of a gas, it becomes more dense. If the temperature is lowered sufficiently it will start to condense into a liquid.
Is there air as we know it beyond the earth's atmosphere?
The Earth's atmosphere gets thinner and thinner as we go away from the earth. It becomes negligible at a point in space. Beyond that, there is no atmosphere, only vaccum.
What is difference a ovu zygote embryo fetus?
There really isn't much difference between a zygote, embryo, and fetus. A zygote forms after fertilization and becomes an embryo, which later becomes a fetus.
What is the definition of central limit theorem?
The central limit theorem basically states that as the sample size gets large enough, the sampling distribution becomes more normal regardless of the population distribution.
