EstimatedDistribution[{0,-1,0,0,1,0,1,1},f[t]]

(*极大似然*)
FindDistributionParameters[{1.5,1.8,2.2,2.5,2.8,1.2},UniformDistribution[{1,1+a}]]

(*矩估计*)
FindDistributionParameters[{1.5,1.8,2.2,2.5,2.8,1.2},UniformDistribution[{1,1+a}],ParameterEstimator->"MethodOfMoments"]

f[t_]=ProbabilityDistribution[Which[
x==-1,t (1-t),
x==0,(1-t)^2,
x==1,t 
],{x}]

f[t_]=ProbabilityDistribution[Which[x==-1,t (1-t),x==0,(((1-t))^2),x==1,t],{x,-1,1,1}]

PDF[dis,x]

-t(1-t)+t//FullSimplify

f[x_]=Which[x==-1,t (1-t),x==0,(((1-t))^2),x==1,t]

f/@{0,-1,0,0,1,0,1,1}

{(((1-t))^2),(1-t) t,(((1-t))^2),(((1-t))^2),t,(((1-t))^2),t,t}//Times@@#&

(((1-t))^9) (t^4)//Maximize[{#,0≤t<=1},t]&

(((1-t))^9) (t^4)//Plot[#,{t,0,1}]&

4/13.

1-(1-t)^2/.t->4/13//N

t(1-t)+(1-t)^2+t//Simplify

Reduce[((2 *3)/(Sqrt[n]))*1.96≤1,n]

Solve[((11.76`)/(Sqrt[n]))≤1&&n∈(Integers),{n}]

Abs@InverseCDF[NormalDistribution[],0.975]