I’m not sure I understand what you’re trying to do, it would be helpful if you could provide a MWE. I’ll take a stab anyway:

I’m assuming you’re trying to perform Pearson’s chi-squared test from HypothesisTests.jl. As the documentation says, it expects either a vector or a matrix of integers, depending on what you are trying to test.

Below an example of how to do this assuming your data is in a DataFrame. Note that the tests I run below might not make any sense whatsoever, as I don’t understand what your data actually is!

```
julia> using DataFrames, HypothesisTests
julia> data = DataFrame(variable = ["Q1","Q2", "Q3"], x1 = [1.47, 1.65, 1993.14], x2 = [1, 1, 1988], x3 = [2,3,9])
julia> ChisqTest(data.x2)
Pearson's Chi-square Test
-------------------------
Population details:
parameter of interest: Multinomial Probabilities
value under h_0: [0.3333333333333333, 0.3333333333333333, 0.3333333333333333]
point estimate: [0.0005025125628140704, 0.0005025125628140704, 0.9989949748743718]
95% confidence interval: Tuple{Float64,Float64}[(0.0, 0.0016), (0.0, 0.0016), (0.998, 1.0)]
(...)
julia> ChisqTest(Matrix(data[:, [:x2, :x3]]))
Pearson's Chi-square Test
-------------------------
Population details:
parameter of interest: Multinomial Probabilities
value under h_0: [0.001486547862359114, 0.001982063816478819, 0.9895453603770503, 1.0458125664837987e-5, 1.3944167553117318e-5, 0.006961625650893821]
point estimate: [0.000499001996007984, 0.000499001996007984, 0.9920159680638723, 0.000998003992015968, 0.0014970059880239522, 0.004491017964071856]
95% confidence interval: Tuple{Float64,Float64}[(0.0, 0.0042), (0.0, 0.0042), (0.989, 0.9957), (0.0, 0.0047), (0.0, 0.0052), (0.0015, 0.0082)]
```