Chi-Squared Test on a table of Binomial Variates - Finding the expected frequencies

In summary, a Chi-Squared test is a statistical method used to determine if there is a significant difference between the observed and expected frequencies in a contingency table. It is commonly used to analyze categorical data and determine if there is a relationship between two variables. It can also be used on a table of Binomial Variates to compare the observed frequencies to a theoretical distribution. The expected frequency in a Chi-Squared test is calculated based on the null hypothesis and the Chi-Squared statistic is then used to determine if the results are statistically significant. The null hypothesis in a Chi-Squared test states that any differences between the observed and expected frequencies are due to chance or random sampling error.
  • #1
Upsidealien
8
0
Hi,

Carry out a chi-squared test for the following table of frequencies of X ∼ Binomial(5,p) variates when (a) p = 0.3

x 0 1 2 3 4 5
Observed 162 346 303 149 36 4
frequency

Now I know how to carry out the chi-squared test once I have found the expected frequencies but the answers states that the frequencies are,

x 0 1 2 3 4 5
Exp(p = 0.3) 168.1 360.2 308.7 132.3 28.4 2.4

What formula did they use to calculate these frequencies?

Thanks
 
Physics news on Phys.org
  • #2


Are you asking for why "expected frequency" is treated the same as "probability"? I haven't checked the table. Is it a table for the binomial probability distribution?
 
  • #3


Hi,

I'm asking how the figured out these expected frequencies..
 

FAQ: Chi-Squared Test on a table of Binomial Variates - Finding the expected frequencies

What is a Chi-Squared Test?

A Chi-Squared test is a statistical method used to determine if there is a significant difference between the observed frequencies and the expected frequencies in a contingency table. It is typically used to analyze categorical data and determine if there is a relationship between two variables.

Why is a Chi-Squared Test used on a table of Binomial Variates?

A Chi-Squared Test can be used on a table of Binomial Variates to determine if the observed frequencies follow a binomial distribution. This is useful in situations where we want to compare the observed data to a theoretical distribution and see if they match.

What is the expected frequency in a Chi-Squared Test?

The expected frequency in a Chi-Squared Test is the number of observations that we would expect to see in each category if the null hypothesis is true. It is calculated by taking the total number of observations and multiplying it by the proportion of each category in the total sample.

How do you calculate the Chi-Squared statistic?

The Chi-Squared statistic is calculated by taking the sum of the squared differences between the observed and expected frequencies, divided by the expected frequencies. This is then compared to a critical value from a Chi-Squared distribution to determine if the results are statistically significant.

What is the null hypothesis in a Chi-Squared Test?

The null hypothesis in a Chi-Squared Test is that there is no significant difference between the observed and expected frequencies. This means that any differences between the two can be attributed to chance or random sampling error. A rejection of the null hypothesis indicates that there is a relationship between the variables being studied.

Back
Top