curl --request POST \
  --url https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova \
  --header 'Authorization: <api-key>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "fromDate": "2020-01-01",
  "toDate": "2022-12-31",
  "filter": [],
  "questionId1": "q60de2bb029a7230061e209f8",
  "questionId2": "q60de2bdeffcabb005be295df-3"
}
'

import requests

url = "https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova"

payload = {
    "fromDate": "2020-01-01",
    "toDate": "2022-12-31",
    "filter": [],
    "questionId1": "q60de2bb029a7230061e209f8",
    "questionId2": "q60de2bdeffcabb005be295df-3"
}
headers = {
    "Authorization": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    fromDate: '2020-01-01',
    toDate: '2022-12-31',
    filter: [],
    questionId1: 'q60de2bb029a7230061e209f8',
    questionId2: 'q60de2bdeffcabb005be295df-3'
  })
};

fetch('https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'fromDate' => '2020-01-01',
    'toDate' => '2022-12-31',
    'filter' => [
        
    ],
    'questionId1' => 'q60de2bb029a7230061e209f8',
    'questionId2' => 'q60de2bdeffcabb005be295df-3'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <api-key>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova"

	payload := strings.NewReader("{\n  \"fromDate\": \"2020-01-01\",\n  \"toDate\": \"2022-12-31\",\n  \"filter\": [],\n  \"questionId1\": \"q60de2bb029a7230061e209f8\",\n  \"questionId2\": \"q60de2bdeffcabb005be295df-3\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova")
  .header("Authorization", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"fromDate\": \"2020-01-01\",\n  \"toDate\": \"2022-12-31\",\n  \"filter\": [],\n  \"questionId1\": \"q60de2bb029a7230061e209f8\",\n  \"questionId2\": \"q60de2bdeffcabb005be295df-3\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://linear-regression-analysis.sightx.io/linear-regression-analysis-service/anova")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"fromDate\": \"2020-01-01\",\n  \"toDate\": \"2022-12-31\",\n  \"filter\": [],\n  \"questionId1\": \"q60de2bb029a7230061e209f8\",\n  \"questionId2\": \"q60de2bdeffcabb005be295df-3\"\n}"

response = http.request(request)
puts response.read_body

{
  "sSBetween": 9,
  "sSWithin": 2.5,
  "sSTotal": 11.5,
  "dfBetween": 3,
  "dfWithin": 4,
  "dfTotal": 7,
  "mSBetween": 3,
  "mSWithin": 0.625,
  "f": 4.8,
  "pValue": 0.08190207264171079,
  "groups": {
    "3.00": [
      3,
      4
    ],
    "2.00": [
      1
    ],
    "1.00": [
      3,
      2,
      1
    ],
    "4.00": [
      4,
      4
    ]
  },
  "tukeyhsd": [
    [
      [
        0,
        1
      ],
      0.18381849101753034
    ],
    [
      [
        0,
        2
      ],
      0.2984621358343368
    ],
    [
      [
        0,
        3
      ],
      0.9164226624660774
    ],
    [
      [
        1,
        2
      ],
      0.7109011294549475
    ],
    [
      [
        1,
        3
      ],
      0.11380425376419612
    ],
    [
      [
        2,
        3
      ],
      0.1537440535960901
    ]
  ],
  "sSgroups": {
    "3.00": 3.5,
    "2.00": 1,
    "1.00": 1.9999999999999998,
    "4.00": 4
  },
  "meansTable": {
    "3.00": {
      "n": 2,
      "mean": 3.5,
      "stdDev": 0.7071067811865476,
      "stdError": 0.5,
      "min": 3,
      "max": 4
    },
    "2.00": {
      "n": 1,
      "mean": 1,
      "stdDev": null,
      "stdError": null,
      "min": 1,
      "max": 1
    },
    "1.00": {
      "n": 3,
      "mean": 2,
      "stdDev": 1,
      "stdError": 0.5773502691896258,
      "min": 1,
      "max": 3
    },
    "4.00": {
      "n": 2,
      "mean": 4,
      "stdDev": 0,
      "stdError": 0,
      "min": 4,
      "max": 4
    },
    "_total_": {
      "n": 8,
      "mean": 2.75,
      "stdDev": 1.2817398889233114,
      "stdError": 0.4531634835874828,
      "min": 1,
      "max": 4
    }
  }
}