Sensor networks have received considerable attention in recent years, and are often employed in the applications where data are difficult or expensive to collect. In these applications, in addition to individual sensor readings, statistical aggregates such as Min and Count over the readings of a group of sensor nodes are often needed. To conserve resources for sensor nodes, in-network strategies are adopted to process the aggregates. One primitive in-network aggregation strategy is the tree-based aggregation, where the aggregates are computed along a spanning tree over a sensor network. However, a shortcoming with the tree-based aggregation is that it is not robust against communication failures, which are common in sensor networks. One of the solutions to overcome this shortcoming is to enable multi-path routing, by which each node broadcasts its reading or a partial aggregate to multiple neighbors. However, multi-path routing based aggregation typically suffers from the problem of overcounting sensor readings. In this study, we propose using the linear counting sketches for multi-path routing based in-network aggregation. We claim that the use of the linear counting sketches makes our approach considerably more accurate than previous approaches using the same sketch space. Our approach also enjoys low variances in term of the aggregate accuracy, and low overheads either in computations or sketch space. Through extensive experiments with real-world and synthetic data, we demonstrate the efficiency and effectiveness of using the linear counting sketches as a solution for the in-network aggregation.