Filter design is all about tradeoffs, so you need to choose the design method that best suits your needs. If this is for a student project, chances are that the nuanced differences between the various design methods do not really have great import for you (although linear phase in the passband is often an important requirement), and a good starting point would be an equiripple FIR filter where you specify the length, cutoff frequency, passband ripple and stopband attenuation.
The length of your filter should reflect your how stationary the input signal is, in general should be much less than the length of your time-series and preferably more than one cycle at the cut-off frequency (for 50Hz cutoff at 1000Hz sample rate, you're probably looking at something between N = 50 and 250).
Reasonable starting points for passband ripple and stopband attenuation are, say, 1dB and 60dB, respectively. But this is really something that you'd typically choose based on the characteristics of your data: what you consider signal, what you consider noise, how strong they tend to be relative to each other.
FilterSpec = fdesign.lowpass('N,Fc,Ap,Ast',50,50,1,60,1000);
FilterObj = design(FilterSpec,'equiripple');
If the transition band isn't narrow enough for your needs, then you can increase the length of the the filter, or relax the passband ripple or stopband attenuation constraints.
Once you're happy with your design, you can apply the filter to your time-series via any of:
FilteredSeries = FilterObj.filter(RawTimeSeries);
FilteredSeries = filter(FilterObj,RawTimeSeries);
FilteredSeries = filter(FilterObj.Numerator,1,RawTimeSeries);
FilteredSeries = conv(RawTimeSeries,FilterObj.Numerator,'valid');
The 3rd and 4th of these only work for FIR filters. You'll probably want to discard the first N values of the filtered series generated by the first three commands (the fourth command already does this because of the 'valid' flag).
For more information, the standard textbook (though I'm not a huge fan) is "Discrete-Time Signal Processing" by Oppenheim & Schafer. This also looks like a good learning resource (see Chapter 14), and maybe this one too.