*Abstract*: Recent advances in information technologies (IT) have powered the merger of online and offline retail channels into one single platform. Modern consumers frequently switch between online and offline channels when they navigate through various stages of the decision journey, motivating multichannel sellers to develop omni-channel strategies that optimize their overall profit. This study examines consumers' cross-channel search behavior of "pseudo-showrooming," or the consumer behavior of inspecting one product at a seller's physical store before buying a related but different product at the same seller's online store, and investigates how such consumer behavior allows a multichannel seller to achieve better coordination between its online and offline arms through optimal product placement strategies.

Participants in the study were grouped into the following categories:

- Where_bought: Where they ended up purchasing an item: bought at the store, bought online.

- Who_bought: If they bought from the same or a different retailer.

Each participant was then measured on:

- Money: how much money they spent in dollars on the product.

- Time: how much time (in minutes) they spent looking at the product online.

1) Give an example of type 1 error based on this study (do not just define, explain in context how it might have happened here).

2) Give an example of type 2 error based on this study (do not just define, explain in context how it might have happened here).

Complete DataSet: I couldn't attach the file.

where_bought who_bought money time

store same 72 5.18

store same 61 3.74

store same 53 6.35

store same 47 4.66

store same 35 2.76

store same 49 5.11

store same 56 4.4

store same 48 4.9

store same 46 3.72

store same 63 5.91

store different 64 5.66

store different 34 3.7

store different 28 5.03

store different 33 4.06

store different 61 5.03

store different 61 4.73

store different 86 5.89

store different 62 4.23

store different 68 4.78

store different 44 5.69

online same 46 0.23

online same 58 1.35

online same 59 0.48

online same 36 1.06

online same 46 1.53

online same 72 1.4

online same 61 0.22

online same 58 2.53

online same 52 2.56

online same 60 0.36

online different 29 2.43

online different 58 1.85

online different 44 2.65

online different 75 2.92

online different 53 1.38

online different 38 0.86

online different 52 2.34

online different 68 2.83

online different 54 0.57

online different 59 0.86

3) What are the conditions in this experiment?

4) For each condition list the means, standard deviations, and standard error for the conditions for time and money spent. Please note that means you should have several sets of M, SD, and SE. Be sure you name the sets of means, sd, and se different things so you can use them later.

5) Which condition appears to have the best model fit using the mean as the model (i.e. smallest error) for time?

6) What are the df for each condition?

7) What is the confidence interval (95%) for the means?

8) Use the MOTE library to calculate the effect size for the difference between money spent for the following comparisons

9) What can you determine about the effect size in the experiment - is it small, medium or large?

10) How many people did we need in the study for each comparison?