The function will fit the Binomial distribution when random variables, corresponding frequencies and probability value are given. It will provide the expected frequencies, chi-squared test statistics value, p value and degree of freedom so that it can be seen if this distribution fits the data.

fitBin(x,obs.freq,p=0)

Arguments

x

vector of binomial random variables.

obs.freq

vector of frequencies.

p

single value for probability.

Value

The output of fitBin gives the class format fitB and fit consisting a list

bin.ran.var binomial random variables.

obs.freq corresponding observed frequencies.

exp.freq corresponding expected frequencies.

statistic chi-squared test statistics value.

df degree of freedom.

p.value probability value by chi-squared test statistic.

fitB fitted probability values of dbinom.

phat estimated probability value.

call the inputs of the function.

Details

$$x = 0,1,2,...$$ $$0 \le p \le 1$$ $$obs.freq \ge 0$$

NOTE : If input parameters are not in given domain conditions necessary error messages will be provided to go further.

Examples

No.D.D <- 0:7 #assigning the random variables Obs.fre.1 <- c(47,54,43,40,40,41,39,95) #assigning the corresponding frequencies #fitting when the random variable,frequencies are given. fitBin(No.D.D,Obs.fre.1)
#> Chi-squared approximation may be doubtful because expected frequency is less than 5
#> Call: #> fitBin(x = No.D.D, obs.freq = Obs.fre.1) #> #> Chi-squared test for Binomial Distribution #> #> Observed Frequency : 47 54 43 40 40 41 39 95 #> #> expected Frequency : 1.59 13.41 48.3 96.68 116.11 83.66 33.49 5.75 #> #> estimated probability value : 0.5456498 #> #> X-squared : 2911.434 ,df : 6 ,p-value : 0