Table 3 Variables used for the COVID-related lifestyle segmentation of Hungarian consumers
From: Growing couch potatoes? The impact of COVID-19 in the light of personal values in Hungary
Variable | Min | Max | Obs | Mean1 | SD | Obs | Mean1 | SD | t test (p value) |
|---|---|---|---|---|---|---|---|---|---|
Pre-COVID scores | Post-COVID scores | ||||||||
Buying local food | 1 | 7 | 993 | 2.96 | 1.3 | 993 | 3.29 | 1.53 | 0.0100 |
Cooking | 1 | 7 | 995 | 2.08 | 1.49 | 995 | 1.98 | 1.37 | 0.0000 |
Eating convenience bakery products for breakfast | 1 | 7 | 998 | 3.84 | 2.01 | 993 | 4.49 | 2.07 | 0.0000 |
Ordering lunch | 1 | 7 | 998 | 5.91 | 1.61 | 999 | 6.06 | 1.65 | 0.0000 |
Ordering dinner | 1 | 7 | 998 | 6.3 | 1.26 | 999 | 6.39 | 1.26 | 0.0036 |
Consuming soft drinks | 1 | 7 | 998 | 4.19 | 2.32 | 998 | 4.32 | 2.38 | 0.0008 |
Enjoying light training | 1 | 7 | 998 | 2.25 | 1.59 | 998 | 2.46 | 1.83 | 0.0003 |
Doing an intense workout | 1 | 7 | 997 | 4.68 | 2.41 | 997 | 4.84 | 2.42 | 0.0076 |