Western Uttar Pradesh
10 seats went to polls on 10th April in this highly polarized region. We tracked almost 60% of those seats closely to get a sample size of a whopping 1893 responses. This was a totally random exercise wherein we did not target any particular caste/religion or economic background during data collection. We used our revolutionary new methodology of RSSI and VWISM to collect data of different ethnic sub groups with the following percentage representation;

We then adjusted these percentages by adding weightage as per our own formula of caste-vote matrix for western UP. For instance, classically, Dalit voters were under represented in our sample size so we added weightage to the same based on our western UP demographic formula which projects Dalits at 17% in this region. Thus, eventually we arrived at the overall vote-share projections for different parties based on superimposing sample-size data on to our caste-vote matrix of west-UP.

Based on our vote-share projections and by analysing the data parity in terms of different assembly segments and polling stations we arrived at the seat-share projections for the first phase of polling in western Uttar Pradesh. We have used a dynamic new methodology of SVV (Segmental Vote-Share Variation) to convert vote-shares to seats wherein we give weightage to difference in vote-share projections of different segments of caste and region to arrive at seat projections. For instance, although BJP emerged as the number one in terms of vote-share, BSP was the first choice of Dalit segment of voters, so we extrapolate this data to different sub-regions and arrive at a mathematical model that projects seats accordingly.

One of the new theories that has been floated in the last few days is that there was Muslim vote consolidation in western UP from seat to seat in order to defeat Modi which was said to be invisible in the overall numbers because Muslim voters had voted for different parties in different parliamentary seats. Based on our number crunching, we can safely say that this is a bogus theory being floated by people who lack even basic understanding of electoral dynamics.

Ghaziabad: Let us look at Ghaziabad as an example to understand the Muslim voting patterns. We had done our ground activities in 3 assembly segments of Ghaziabad parliamentary constituency and had polled 61 Muslim voters. Although BSP had polled a lion’s share of the Muslim vote, it was nowhere close to being termed as “total consolidation to defeat Modi”. Muslim vote in the past has seen to be a near 100% consolidated vote mostly to defeat BJP, but this time somehow there seems to be a lot of confusion among the Muslim thought leadership (read as Mullahs and Maulvis) on which party to vote for. This confusion is reflected in the Muslim vote of west UP too. Whether such a confusion holds in the future phases remains to be seen.

We had a sample size of 1623 spread across 10 assembly segments of 3 parliamentary constituencies out of the 6 that went to polls on the 10th of April in Bihar. Once again this was a wholly random sample chosen from specific polling booths using our path-breaking methodology to arrive at the right mix of polling stations in the right assembly segments.

We then added weightage to the above data based on the census data of different social profiles and also based on the weightage of different voting sub groups. Using our own mathematical modelling we then converted the actual vote-shares into seat shares. This entire exercise carries a error margin of less than 2% as our sample sizes are large and geographically spread out which allows us to extrapolate the data accordingly to different sub categories.

One interesting aspect of Bihar has been the Dalit vote which seems to have gone to the BJP in a big way. BJP’s decision to ally with Ram Vilas Paswan seems to have worked on the ground and the much feared upper caste anger for BJP’s Dalit move hasn’t really happened. There is also a section of Dalit vote which is probably voting for Modi’s brand of development politics. Surprisingly among Yadavs too BJP seems to be getting equal traction vis-à-vis RJD-Congress combine.

Madhya Pradesh
We had a sample size of 951 in Madhya Pradesh which was spread across 9 assembly segments of 4 MP seats. We ensured adequate social representation to all castes by using our unique methodology and also added weightage later on based on our mathematical modelling of census data. Following are the findings of Madhya Pradesh in phase 1.

[Note: In the next part we will analyse Maharashtra, Haryana and Delhi and also come up with full projections for April 10th polling]